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https://github.com/curioustorvald/tsvm.git
synced 2026-03-07 19:51:51 +09:00
TAV with ICtCp colour space
This commit is contained in:
minjaesong
@@ -12,7 +12,6 @@ import net.torvald.terrarum.modulecomputers.virtualcomputer.tvd.toUint
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import net.torvald.tsvm.peripheral.GraphicsAdapter
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import net.torvald.tsvm.peripheral.PeriBase
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import net.torvald.tsvm.peripheral.fmod
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import net.torvald.util.Float16
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import kotlin.math.*
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class GraphicsJSR223Delegate(private val vm: VM) {
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@@ -2176,14 +2175,14 @@ class GraphicsJSR223Delegate(private val vm: VM) {
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val Sp = I + 1.0212710798422344 * Ct - 0.6052744909924316 * Cp
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// HLG decode: L'M'S' -> linear LMS
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val L = HLG_inverse_OETF(Lp)
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val M = HLG_inverse_OETF(Mp)
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val S = HLG_inverse_OETF(Sp)
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val L = HLG_EOTF(Lp)
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val M = HLG_EOTF(Mp)
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val S = HLG_EOTF(Sp)
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// LMS -> linear sRGB (inverse matrix)
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val rLin = 3.436606694333079 * L -2.5064521186562705 * M + 0.06984542432319149 * S
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val gLin = -0.7913295555989289 * L + 1.983600451792291 * M -0.192270896193362 * S
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val bLin = -0.025949899690592665 * L -0.09891371471172647 * M + 1.1248636144023192 * S
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val rLin = 6.1723815689243215 * L -5.319534979827695 * M + 0.14699442094633924 * S
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val gLin = -1.3243428148026244 * L + 2.560286104841917 * M -0.2359203727576164 * S
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val bLin = -0.011819739235953752 * L -0.26473549971186555 * M + 1.2767952602537955 * S
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// Gamma encode to sRGB
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val rSrgb = srgbUnlinearize(rLin)
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@@ -2204,7 +2203,7 @@ class GraphicsJSR223Delegate(private val vm: VM) {
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// Helper functions for ICtCp decoding
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// Inverse HLG OETF (HLG -> linear)
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fun HLG_inverse_OETF(V: Double): Double {
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fun HLG_EOTF(V: Double): Double {
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val a = 0.17883277
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val b = 1.0 - 4.0 * a
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val c = 0.5 - a * ln(4.0 * a)
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@@ -3919,4 +3918,665 @@ class GraphicsJSR223Delegate(private val vm: VM) {
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}
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}
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// ================= TAV (TSVM Advanced Video) Decoder =================
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// DWT-based video codec with ICtCp color space support
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fun tavDecode(blockDataPtr: Long, currentRGBAddr: Long, prevRGBAddr: Long,
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width: Int, height: Int, qY: Int, qCo: Int, qCg: Int, frameCounter: Int,
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debugMotionVectors: Boolean = false, waveletFilter: Int = 1,
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decompLevels: Int = 3, enableDeblocking: Boolean = true,
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isLossless: Boolean = false, tavVersion: Int = 1) {
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var readPtr = blockDataPtr
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try {
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val tilesX = (width + 63) / 64 // 64x64 tiles
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val tilesY = (height + 63) / 64
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// Process each tile
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for (tileY in 0 until tilesY) {
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for (tileX in 0 until tilesX) {
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// Read tile header (9 bytes: mode + mvX + mvY + rcf)
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val mode = vm.peek(readPtr).toInt() and 0xFF
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readPtr += 1
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val mvX = vm.peekShort(readPtr).toInt()
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readPtr += 2
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val mvY = vm.peekShort(readPtr).toInt()
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readPtr += 2
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val rcf = vm.peekFloat(readPtr)
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readPtr += 4
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when (mode) {
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0x00 -> { // TAV_MODE_SKIP
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// Copy 64x64 tile from previous frame to current frame
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copyTile64x64RGB(tileX, tileY, currentRGBAddr, prevRGBAddr, width, height)
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}
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0x01 -> { // TAV_MODE_INTRA
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// Decode DWT coefficients directly to RGB buffer
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readPtr = decodeDWTIntraTileRGB(readPtr, tileX, tileY, currentRGBAddr,
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width, height, qY, qCo, qCg, rcf,
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waveletFilter, decompLevels, isLossless, tavVersion)
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}
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0x02 -> { // TAV_MODE_INTER
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// Motion compensation + DWT residual to RGB buffer
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readPtr = decodeDWTInterTileRGB(readPtr, tileX, tileY, mvX, mvY,
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currentRGBAddr, prevRGBAddr,
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width, height, qY, qCo, qCg, rcf,
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waveletFilter, decompLevels, isLossless, tavVersion)
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}
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0x03 -> { // TAV_MODE_MOTION
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// Motion compensation only (no residual)
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applyMotionCompensation64x64RGB(tileX, tileY, mvX, mvY,
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currentRGBAddr, prevRGBAddr, width, height)
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}
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}
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}
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}
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} catch (e: Exception) {
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println("TAV decode error: ${e.message}")
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}
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}
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private fun decodeDWTIntraTileRGB(readPtr: Long, tileX: Int, tileY: Int, currentRGBAddr: Long,
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width: Int, height: Int, qY: Int, qCo: Int, qCg: Int, rcf: Float,
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waveletFilter: Int, decompLevels: Int, isLossless: Boolean, tavVersion: Int): Long {
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val tileSize = 64
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val coeffCount = tileSize * tileSize
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var ptr = readPtr
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// Read quantized DWT coefficients for Y, Co, Cg channels
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val quantizedY = ShortArray(coeffCount)
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val quantizedCo = ShortArray(coeffCount)
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val quantizedCg = ShortArray(coeffCount)
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// Read Y coefficients
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for (i in 0 until coeffCount) {
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quantizedY[i] = vm.peekShort(ptr)
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ptr += 2
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}
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// Read Co coefficients
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for (i in 0 until coeffCount) {
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quantizedCo[i] = vm.peekShort(ptr)
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ptr += 2
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}
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// Read Cg coefficients
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for (i in 0 until coeffCount) {
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quantizedCg[i] = vm.peekShort(ptr)
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ptr += 2
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}
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// Dequantize and apply inverse DWT
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val yTile = FloatArray(coeffCount)
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val coTile = FloatArray(coeffCount)
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val cgTile = FloatArray(coeffCount)
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for (i in 0 until coeffCount) {
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yTile[i] = quantizedY[i] * qY * rcf
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coTile[i] = quantizedCo[i] * qCo * rcf
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cgTile[i] = quantizedCg[i] * qCg * rcf
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}
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// Apply inverse DWT using specified filter with decomposition levels
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if (isLossless) {
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applyDWTInverseMultiLevel(yTile, tileSize, tileSize, decompLevels, 0)
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applyDWTInverseMultiLevel(coTile, tileSize, tileSize, decompLevels, 0)
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applyDWTInverseMultiLevel(cgTile, tileSize, tileSize, decompLevels, 0)
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} else {
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applyDWTInverseMultiLevel(yTile, tileSize, tileSize, decompLevels, waveletFilter)
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applyDWTInverseMultiLevel(coTile, tileSize, tileSize, decompLevels, waveletFilter)
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applyDWTInverseMultiLevel(cgTile, tileSize, tileSize, decompLevels, waveletFilter)
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}
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// Convert to RGB based on TAV version (YCoCg-R for v1, ICtCp for v2)
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if (tavVersion == 2) {
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convertICtCpTileToRGB(tileX, tileY, yTile, coTile, cgTile, currentRGBAddr, width, height)
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} else {
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convertYCoCgTileToRGB(tileX, tileY, yTile, coTile, cgTile, currentRGBAddr, width, height)
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}
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return ptr
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}
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private fun convertYCoCgTileToRGB(tileX: Int, tileY: Int, yTile: FloatArray, coTile: FloatArray, cgTile: FloatArray,
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rgbAddr: Long, width: Int, height: Int) {
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val tileSize = 64
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val startX = tileX * tileSize
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val startY = tileY * tileSize
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for (y in 0 until tileSize) {
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for (x in 0 until tileSize) {
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val frameX = startX + x
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val frameY = startY + y
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if (frameX < width && frameY < height) {
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val tileIdx = y * tileSize + x
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val pixelIdx = frameY * width + frameX
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// YCoCg-R to RGB conversion (exact inverse of encoder)
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val Y = yTile[tileIdx]
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val Co = coTile[tileIdx]
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val Cg = cgTile[tileIdx]
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// Inverse of encoder's YCoCg-R transform:
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val tmp = Y - Cg / 2.0f
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val g = Cg + tmp
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val b = tmp - Co / 2.0f
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val r = Co + b
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val rgbOffset = pixelIdx * 3L
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vm.poke(rgbAddr + rgbOffset, r.toInt().coerceIn(0, 255).toByte())
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vm.poke(rgbAddr + rgbOffset + 1, g.toInt().coerceIn(0, 255).toByte())
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vm.poke(rgbAddr + rgbOffset + 2, b.toInt().coerceIn(0, 255).toByte())
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}
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}
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}
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}
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private fun convertICtCpTileToRGB(tileX: Int, tileY: Int, iTile: FloatArray, ctTile: FloatArray, cpTile: FloatArray,
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rgbAddr: Long, width: Int, height: Int) {
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val tileSize = 64
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val startX = tileX * tileSize
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val startY = tileY * tileSize
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for (y in 0 until tileSize) {
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for (x in 0 until tileSize) {
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val frameX = startX + x
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val frameY = startY + y
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if (frameX < width && frameY < height) {
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val tileIdx = y * tileSize + x
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val pixelIdx = frameY * width + frameX
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// ICtCp to sRGB conversion (adapted from encoder ICtCp functions)
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val I = iTile[tileIdx].toDouble() / 255.0
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val Ct = (ctTile[tileIdx].toDouble() - 127.5) / 255.0
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val Cp = (cpTile[tileIdx].toDouble() - 127.5) / 255.0
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// ICtCp -> L'M'S' (inverse matrix)
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val Lp = I + 0.015718580108730416 * Ct + 0.2095810681164055 * Cp
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val Mp = I - 0.015718580108730416 * Ct - 0.20958106811640548 * Cp
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val Sp = I + 1.0212710798422344 * Ct - 0.6052744909924316 * Cp
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// HLG decode: L'M'S' -> linear LMS
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val L = HLG_EOTF(Lp)
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val M = HLG_EOTF(Mp)
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val S = HLG_EOTF(Sp)
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// LMS -> linear sRGB (inverse matrix)
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val rLin = 6.1723815689243215 * L -5.319534979827695 * M + 0.14699442094633924 * S
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val gLin = -1.3243428148026244 * L + 2.560286104841917 * M -0.2359203727576164 * S
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val bLin = -0.011819739235953752 * L -0.26473549971186555 * M + 1.2767952602537955 * S
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// Gamma encode to sRGB
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val rSrgb = srgbUnlinearize(rLin)
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val gSrgb = srgbUnlinearize(gLin)
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val bSrgb = srgbUnlinearize(bLin)
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val rgbOffset = pixelIdx * 3L
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vm.poke(rgbAddr + rgbOffset, (rSrgb * 255.0).toInt().coerceIn(0, 255).toByte())
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vm.poke(rgbAddr + rgbOffset + 1, (gSrgb * 255.0).toInt().coerceIn(0, 255).toByte())
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vm.poke(rgbAddr + rgbOffset + 2, (bSrgb * 255.0).toInt().coerceIn(0, 255).toByte())
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}
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}
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}
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}
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private fun addYCoCgResidualToRGBTile(tileX: Int, tileY: Int, yRes: FloatArray, coRes: FloatArray, cgRes: FloatArray,
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rgbAddr: Long, width: Int, height: Int) {
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val tileSize = 64
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val startX = tileX * tileSize
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val startY = tileY * tileSize
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for (y in 0 until tileSize) {
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for (x in 0 until tileSize) {
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val frameX = startX + x
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val frameY = startY + y
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if (frameX < width && frameY < height) {
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val tileIdx = y * tileSize + x
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val pixelIdx = frameY * width + frameX
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val rgbOffset = pixelIdx * 3L
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// Get current RGB (from motion compensation)
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val curR = (vm.peek(rgbAddr + rgbOffset).toInt() and 0xFF).toFloat()
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val curG = (vm.peek(rgbAddr + rgbOffset + 1).toInt() and 0xFF).toFloat()
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val curB = (vm.peek(rgbAddr + rgbOffset + 2).toInt() and 0xFF).toFloat()
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// Convert current RGB back to YCoCg
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val co = (curR - curB) / 2
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val tmp = curB + co
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val cg = (curG - tmp) / 2
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val yPred = tmp + cg
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// Add residual
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val yFinal = yPred + yRes[tileIdx]
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val coFinal = co + coRes[tileIdx]
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val cgFinal = cg + cgRes[tileIdx]
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// Convert back to RGB
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val tmpFinal = yFinal - cgFinal
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val gFinal = yFinal + cgFinal
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val bFinal = tmpFinal - coFinal
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val rFinal = tmpFinal + coFinal
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vm.poke(rgbAddr + rgbOffset, rFinal.toInt().coerceIn(0, 255).toByte())
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vm.poke(rgbAddr + rgbOffset + 1, gFinal.toInt().coerceIn(0, 255).toByte())
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vm.poke(rgbAddr + rgbOffset + 2, bFinal.toInt().coerceIn(0, 255).toByte())
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}
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}
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}
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}
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// Helper functions (simplified versions of existing DWT functions)
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private fun copyTile64x64RGB(tileX: Int, tileY: Int, currentRGBAddr: Long, prevRGBAddr: Long, width: Int, height: Int) {
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val tileSize = 64
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val startX = tileX * tileSize
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val startY = tileY * tileSize
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for (y in 0 until tileSize) {
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for (x in 0 until tileSize) {
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val frameX = startX + x
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val frameY = startY + y
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if (frameX < width && frameY < height) {
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val pixelIdx = frameY * width + frameX
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val rgbOffset = pixelIdx * 3L
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// Copy RGB pixel from previous frame
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val r = vm.peek(prevRGBAddr + rgbOffset)
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val g = vm.peek(prevRGBAddr + rgbOffset + 1)
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val b = vm.peek(prevRGBAddr + rgbOffset + 2)
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vm.poke(currentRGBAddr + rgbOffset, r)
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vm.poke(currentRGBAddr + rgbOffset + 1, g)
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vm.poke(currentRGBAddr + rgbOffset + 2, b)
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}
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}
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}
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}
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private fun decodeDWTInterTileRGB(readPtr: Long, tileX: Int, tileY: Int, mvX: Int, mvY: Int,
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currentRGBAddr: Long, prevRGBAddr: Long,
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width: Int, height: Int, qY: Int, qCo: Int, qCg: Int, rcf: Float,
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waveletFilter: Int, decompLevels: Int, isLossless: Boolean, tavVersion: Int): Long {
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// Step 1: Apply motion compensation
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applyMotionCompensation64x64RGB(tileX, tileY, mvX, mvY, currentRGBAddr, prevRGBAddr, width, height)
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// Step 2: Add DWT residual (same as intra but add to existing pixels)
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return decodeDWTIntraTileRGB(readPtr, tileX, tileY, currentRGBAddr, width, height, qY, qCo, qCg, rcf,
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waveletFilter, decompLevels, isLossless, tavVersion)
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}
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private fun applyMotionCompensation64x64RGB(tileX: Int, tileY: Int, mvX: Int, mvY: Int,
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currentRGBAddr: Long, prevRGBAddr: Long,
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width: Int, height: Int) {
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val tileSize = 64
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val startX = tileX * tileSize
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val startY = tileY * tileSize
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// Motion vectors in quarter-pixel precision
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val refX = startX + (mvX / 4.0f)
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val refY = startY + (mvY / 4.0f)
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for (y in 0 until tileSize) {
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for (x in 0 until tileSize) {
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val currentPixelIdx = (startY + y) * width + (startX + x)
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if (currentPixelIdx >= 0 && currentPixelIdx < width * height) {
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// Bilinear interpolation for sub-pixel motion vectors
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val srcX = refX + x
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val srcY = refY + y
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val interpolatedRGB = bilinearInterpolateRGB(prevRGBAddr, width, height, srcX, srcY)
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val rgbOffset = currentPixelIdx * 3L
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vm.poke(currentRGBAddr + rgbOffset, interpolatedRGB[0])
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vm.poke(currentRGBAddr + rgbOffset + 1, interpolatedRGB[1])
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vm.poke(currentRGBAddr + rgbOffset + 2, interpolatedRGB[2])
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}
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}
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}
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}
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private fun bilinearInterpolateRGB(rgbPtr: Long, width: Int, height: Int, x: Float, y: Float): ByteArray {
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val x0 = kotlin.math.floor(x).toInt()
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val y0 = kotlin.math.floor(y).toInt()
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val x1 = x0 + 1
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val y1 = y0 + 1
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if (x0 < 0 || y0 < 0 || x1 >= width || y1 >= height) {
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return byteArrayOf(0, 0, 0) // Out of bounds - return black
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}
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val fx = x - x0
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val fy = y - y0
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// Get 4 corner pixels
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val rgb00 = getRGBPixel(rgbPtr, y0 * width + x0)
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val rgb10 = getRGBPixel(rgbPtr, y0 * width + x1)
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val rgb01 = getRGBPixel(rgbPtr, y1 * width + x0)
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val rgb11 = getRGBPixel(rgbPtr, y1 * width + x1)
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// Bilinear interpolation
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val result = ByteArray(3)
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for (c in 0..2) {
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val interp = (1 - fx) * (1 - fy) * (rgb00[c].toInt() and 0xFF) +
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fx * (1 - fy) * (rgb10[c].toInt() and 0xFF) +
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(1 - fx) * fy * (rgb01[c].toInt() and 0xFF) +
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fx * fy * (rgb11[c].toInt() and 0xFF)
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result[c] = interp.toInt().coerceIn(0, 255).toByte()
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}
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return result
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}
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private fun getRGBPixel(rgbPtr: Long, pixelIdx: Int): ByteArray {
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val offset = pixelIdx * 3L
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return byteArrayOf(
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vm.peek(rgbPtr + offset),
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vm.peek(rgbPtr + offset + 1),
|
||||
vm.peek(rgbPtr + offset + 2)
|
||||
)
|
||||
}
|
||||
|
||||
private fun applyDWT53Forward(data: FloatArray, width: Int, height: Int) {
|
||||
// TODO: Implement 5/3 forward DWT
|
||||
// Lifting scheme implementation for 5/3 reversible filter
|
||||
}
|
||||
|
||||
private fun applyDWT53Inverse(data: FloatArray, width: Int, height: Int) {
|
||||
// 5/3 reversible DWT inverse using lifting scheme
|
||||
// First apply horizontal inverse DWT on all rows
|
||||
val tempRow = FloatArray(width)
|
||||
for (y in 0 until height) {
|
||||
for (x in 0 until width) {
|
||||
tempRow[x] = data[y * width + x]
|
||||
}
|
||||
applyLift53InverseHorizontal(tempRow, width)
|
||||
for (x in 0 until width) {
|
||||
data[y * width + x] = tempRow[x]
|
||||
}
|
||||
}
|
||||
|
||||
// Then apply vertical inverse DWT on all columns
|
||||
val tempCol = FloatArray(height)
|
||||
for (x in 0 until width) {
|
||||
for (y in 0 until height) {
|
||||
tempCol[y] = data[y * width + x]
|
||||
}
|
||||
applyLift53InverseVertical(tempCol, height)
|
||||
for (y in 0 until height) {
|
||||
data[y * width + x] = tempCol[y]
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private fun applyDWT97Forward(data: FloatArray, width: Int, height: Int) {
|
||||
// TODO: Implement 9/7 forward DWT
|
||||
// Lifting scheme implementation for 9/7 irreversible filter
|
||||
}
|
||||
|
||||
private fun applyDWTInverseMultiLevel(data: FloatArray, width: Int, height: Int, levels: Int, filterType: Int) {
|
||||
// Multi-level inverse DWT - reconstruct from smallest to largest (reverse of encoder)
|
||||
val size = width // Full tile size (64)
|
||||
val tempRow = FloatArray(size)
|
||||
val tempCol = FloatArray(size)
|
||||
|
||||
for (level in levels - 1 downTo 0) {
|
||||
val currentSize = size shr level
|
||||
if (currentSize < 2) break
|
||||
|
||||
// Apply inverse DWT to current subband region - EXACT match to encoder
|
||||
// The encoder does ROW transform first, then COLUMN transform
|
||||
// So inverse must do COLUMN inverse first, then ROW inverse
|
||||
|
||||
// Column inverse transform first
|
||||
for (x in 0 until currentSize) {
|
||||
for (y in 0 until currentSize) {
|
||||
tempCol[y] = data[y * size + x]
|
||||
}
|
||||
|
||||
if (filterType == 0) {
|
||||
applyDWT53Inverse1D(tempCol, currentSize)
|
||||
} else {
|
||||
applyDWT97Inverse1D(tempCol, currentSize)
|
||||
}
|
||||
|
||||
for (y in 0 until currentSize) {
|
||||
data[y * size + x] = tempCol[y]
|
||||
}
|
||||
}
|
||||
|
||||
// Row inverse transform second
|
||||
for (y in 0 until currentSize) {
|
||||
for (x in 0 until currentSize) {
|
||||
tempRow[x] = data[y * size + x]
|
||||
}
|
||||
|
||||
if (filterType == 0) {
|
||||
applyDWT53Inverse1D(tempRow, currentSize)
|
||||
} else {
|
||||
applyDWT97Inverse1D(tempRow, currentSize)
|
||||
}
|
||||
|
||||
for (x in 0 until currentSize) {
|
||||
data[y * size + x] = tempRow[x]
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private fun applyDWT97Inverse(data: FloatArray, width: Int, height: Int) {
|
||||
// 9/7 irreversible DWT inverse using lifting scheme
|
||||
// First apply horizontal inverse DWT on all rows
|
||||
val tempRow = FloatArray(width)
|
||||
for (y in 0 until height) {
|
||||
for (x in 0 until width) {
|
||||
tempRow[x] = data[y * width + x]
|
||||
}
|
||||
applyLift97InverseHorizontal(tempRow, width)
|
||||
for (x in 0 until width) {
|
||||
data[y * width + x] = tempRow[x]
|
||||
}
|
||||
}
|
||||
|
||||
// Then apply vertical inverse DWT on all columns
|
||||
val tempCol = FloatArray(height)
|
||||
for (x in 0 until width) {
|
||||
for (y in 0 until height) {
|
||||
tempCol[y] = data[y * width + x]
|
||||
}
|
||||
applyLift97InverseVertical(tempCol, height)
|
||||
for (y in 0 until height) {
|
||||
data[y * width + x] = tempCol[y]
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private fun applyLift97InverseHorizontal(row: FloatArray, width: Int) { TODO() }
|
||||
private fun applyLift97InverseVertical(col: FloatArray, height: Int) { TODO() }
|
||||
|
||||
// 1D lifting scheme implementations for 5/3 filter
|
||||
private fun applyLift53InverseHorizontal(data: FloatArray, length: Int) {
|
||||
if (length < 2) return
|
||||
|
||||
val temp = FloatArray(length)
|
||||
val half = (length + 1) / 2
|
||||
|
||||
// Separate even and odd samples (inverse interleaving)
|
||||
for (i in 0 until half) {
|
||||
temp[i] = data[2 * i] // Even samples (low-pass)
|
||||
}
|
||||
for (i in 0 until length / 2) {
|
||||
temp[half + i] = data[2 * i + 1] // Odd samples (high-pass)
|
||||
}
|
||||
|
||||
// Inverse lifting steps for 5/3 filter
|
||||
// Step 2: Undo update step - even[i] -= (odd[i-1] + odd[i] + 2) >> 2
|
||||
for (i in 1 until half) {
|
||||
val oddPrev = if (i - 1 >= 0) temp[half + i - 1] else 0.0f
|
||||
val oddCurr = if (i < length / 2) temp[half + i] else 0.0f
|
||||
temp[i] += (oddPrev + oddCurr + 2.0f) / 4.0f
|
||||
}
|
||||
if (half > 0) {
|
||||
val oddCurr = if (0 < length / 2) temp[half] else 0.0f
|
||||
temp[0] += oddCurr / 2.0f
|
||||
}
|
||||
|
||||
// Step 1: Undo predict step - odd[i] += (even[i] + even[i+1]) >> 1
|
||||
for (i in 0 until length / 2) {
|
||||
val evenCurr = temp[i]
|
||||
val evenNext = if (i + 1 < half) temp[i + 1] else temp[half - 1]
|
||||
temp[half + i] -= (evenCurr + evenNext) / 2.0f
|
||||
}
|
||||
|
||||
// Interleave back
|
||||
for (i in 0 until half) {
|
||||
data[2 * i] = temp[i]
|
||||
}
|
||||
for (i in 0 until length / 2) {
|
||||
data[2 * i + 1] = temp[half + i]
|
||||
}
|
||||
}
|
||||
|
||||
private fun applyLift53InverseVertical(data: FloatArray, length: Int) {
|
||||
// Same as horizontal but for vertical direction
|
||||
applyLift53InverseHorizontal(data, length)
|
||||
}
|
||||
|
||||
// 1D lifting scheme implementations for 9/7 irreversible filter
|
||||
private fun applyDWT97Inverse1D(data: FloatArray, length: Int) {
|
||||
if (length < 2) return
|
||||
|
||||
val temp = FloatArray(length)
|
||||
val half = length / 2
|
||||
|
||||
// Split into low and high frequency components (matching encoder layout)
|
||||
// After forward DWT: first half = low-pass, second half = high-pass
|
||||
for (i in 0 until half) {
|
||||
temp[i] = data[i] // Low-pass coefficients (first half)
|
||||
temp[half + i] = data[half + i] // High-pass coefficients (second half)
|
||||
}
|
||||
|
||||
// 9/7 inverse lifting coefficients (exactly matching encoder)
|
||||
val alpha = -1.586134342f
|
||||
val beta = -0.052980118f
|
||||
val gamma = 0.882911076f
|
||||
val delta = 0.443506852f
|
||||
val K = 1.230174105f
|
||||
|
||||
// Inverse lifting steps (undo forward steps in reverse order)
|
||||
|
||||
// Step 5: Undo scaling (reverse of encoder's final step)
|
||||
for (i in 0 until half) {
|
||||
temp[i] /= K // Undo temp[i] *= K
|
||||
temp[half + i] *= K // Undo temp[half + i] /= K
|
||||
}
|
||||
|
||||
// Step 4: Undo update step (delta)
|
||||
for (i in 0 until half) {
|
||||
val left = if (i > 0) temp[half + i - 1] else temp[half + i]
|
||||
val right = if (i < half - 1) temp[half + i + 1] else temp[half + i]
|
||||
temp[i] -= delta * (left + right)
|
||||
}
|
||||
|
||||
// Step 3: Undo predict step (gamma)
|
||||
for (i in 0 until half) {
|
||||
val left = if (i > 0) temp[i - 1] else temp[i]
|
||||
val right = if (i < half - 1) temp[i + 1] else temp[i]
|
||||
temp[half + i] -= gamma * (left + right)
|
||||
}
|
||||
|
||||
// Step 2: Undo update step (beta)
|
||||
for (i in 0 until half) {
|
||||
val left = if (i > 0) temp[half + i - 1] else temp[half + i]
|
||||
val right = if (i < half - 1) temp[half + i + 1] else temp[half + i]
|
||||
temp[i] -= beta * (left + right)
|
||||
}
|
||||
|
||||
// Step 1: Undo predict step (alpha)
|
||||
for (i in 0 until half) {
|
||||
val left = if (i > 0) temp[i - 1] else temp[i]
|
||||
val right = if (i < half - 1) temp[i + 1] else temp[i]
|
||||
temp[half + i] -= alpha * (left + right)
|
||||
}
|
||||
|
||||
// Merge back (inverse of encoder's split)
|
||||
for (i in 0 until half) {
|
||||
data[2 * i] = temp[i] // Even positions get low-pass
|
||||
if (2 * i + 1 < length) {
|
||||
data[2 * i + 1] = temp[half + i] // Odd positions get high-pass
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private fun applyDWT53Inverse1D(data: FloatArray, length: Int) {
|
||||
if (length < 2) return
|
||||
|
||||
val temp = FloatArray(length)
|
||||
val half = length / 2
|
||||
|
||||
// Split into low and high frequency components (matching encoder layout)
|
||||
for (i in 0 until half) {
|
||||
temp[i] = data[i] // Low-pass coefficients (first half)
|
||||
temp[half + i] = data[half + i] // High-pass coefficients (second half)
|
||||
}
|
||||
|
||||
// 5/3 inverse lifting (undo forward steps in reverse order)
|
||||
|
||||
// Step 2: Undo update step (1/4 coefficient)
|
||||
for (i in 0 until half) {
|
||||
val left = if (i > 0) temp[half + i - 1] else 0.0f
|
||||
val right = if (i < half - 1) temp[half + i] else 0.0f
|
||||
temp[i] -= 0.25f * (left + right)
|
||||
}
|
||||
|
||||
// Step 1: Undo predict step (1/2 coefficient)
|
||||
for (i in 0 until half) {
|
||||
val left = temp[i]
|
||||
val right = if (i < half - 1) temp[i + 1] else temp[i]
|
||||
temp[half + i] -= 0.5f * (left + right)
|
||||
}
|
||||
|
||||
// Merge back (inverse of encoder's split)
|
||||
for (i in 0 until half) {
|
||||
data[2 * i] = temp[i] // Even positions get low-pass
|
||||
if (2 * i + 1 < length) {
|
||||
data[2 * i + 1] = temp[half + i] // Odd positions get high-pass
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private fun bilinearInterpolate(
|
||||
dataPtr: Long, width: Int, height: Int,
|
||||
x: Float, y: Float
|
||||
): Float {
|
||||
val x0 = floor(x).toInt()
|
||||
val y0 = floor(y).toInt()
|
||||
val x1 = x0 + 1
|
||||
val y1 = y0 + 1
|
||||
|
||||
if (x0 < 0 || y0 < 0 || x1 >= width || y1 >= height) {
|
||||
return 0.0f // Out of bounds
|
||||
}
|
||||
|
||||
val fx = x - x0
|
||||
val fy = y - y0
|
||||
|
||||
val p00 = vm.peekFloat(dataPtr + (y0 * width + x0) * 4L)!!
|
||||
val p10 = vm.peekFloat(dataPtr + (y0 * width + x1) * 4L)!!
|
||||
val p01 = vm.peekFloat(dataPtr + (y1 * width + x0) * 4L)!!
|
||||
val p11 = vm.peekFloat(dataPtr + (y1 * width + x1) * 4L)!!
|
||||
|
||||
return p00 * (1 - fx) * (1 - fy) +
|
||||
p10 * fx * (1 - fy) +
|
||||
p01 * (1 - fx) * fy +
|
||||
p11 * fx * fy
|
||||
}
|
||||
|
||||
}
|
||||
Reference in New Issue
Block a user