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more lazy q table prep

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minjaesong
2025-08-23 20:12:35 +09:00
parent 6f6d10cc1b
commit f1dab59495
2 changed files with 59 additions and 595 deletions
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tsvm_core/src/net/torvald/tsvm/GraphicsJSR223Delegate.kt
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@@ -1270,324 +1270,39 @@ class GraphicsJSR223Delegate(private val vm: VM) {
// TEV (TSVM Enhanced Video) format support
// Created by Claude on 2025-08-17
private val QUANT_MULT_Y = intArrayOf(40, 20, 10, 8, 6, 5, 4, 1)
private val QUANT_MULT_CO = intArrayOf(40, 20, 10, 8, 6, 5, 4, 1)
private val QUANT_MULT_CG = intArrayOf(80, 40, 20, 16, 12, 10, 8, 2)
// Quality settings for quantization (Y channel) - 16x16 tables
var QUANT_TABLES_Y: Array<IntArray> = arrayOf( // Quality 0 (lowest) - 16x16 table
intArrayOf(
80, 60, 50, 80, 120, 200, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
55, 60, 70, 95, 130, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
70, 65, 80, 120, 200, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
70, 85, 110, 145, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
90, 110, 185, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
120, 175, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
245, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255
), // Quality 1
intArrayOf(
40, 30, 25, 40, 60, 100, 128, 150, 128, 150, 180, 200, 220, 240, 250, 255,
28, 30, 35, 48, 65, 128, 150, 180, 150, 180, 200, 220, 240, 250, 255, 255,
35, 33, 40, 60, 100, 128, 150, 180, 150, 180, 200, 220, 240, 250, 255, 255,
35, 43, 55, 73, 128, 150, 180, 200, 180, 200, 220, 240, 250, 255, 255, 255,
45, 55, 93, 128, 150, 180, 200, 220, 200, 220, 240, 250, 255, 255, 255, 255,
60, 88, 128, 150, 180, 200, 220, 240, 220, 240, 250, 255, 255, 255, 255, 255,
123, 128, 150, 180, 200, 220, 240, 250, 240, 250, 255, 255, 255, 255, 255, 255,
128, 150, 180, 200, 220, 240, 250, 255, 250, 255, 255, 255, 255, 255, 255, 255,
128, 150, 180, 200, 220, 240, 250, 255, 250, 255, 255, 255, 255, 255, 255, 255,
150, 180, 200, 220, 240, 250, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
180, 200, 220, 240, 250, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
200, 220, 240, 250, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
220, 240, 250, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
240, 250, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
250, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255
), // Quality 2
intArrayOf(
20, 15, 13, 20, 30, 50, 64, 75, 64, 75, 90, 100, 110, 120, 125, 128,
14, 15, 18, 24, 33, 64, 75, 90, 75, 90, 100, 110, 120, 125, 128, 140,
18, 17, 20, 30, 50, 64, 75, 90, 75, 90, 100, 110, 120, 125, 128, 140,
18, 22, 28, 37, 64, 75, 90, 100, 90, 100, 110, 120, 125, 128, 140, 150,
23, 28, 47, 64, 75, 90, 100, 110, 100, 110, 120, 125, 128, 140, 150, 160,
30, 44, 64, 75, 90, 100, 110, 120, 110, 120, 125, 128, 140, 150, 160, 170,
62, 64, 75, 90, 100, 110, 120, 125, 120, 125, 128, 140, 150, 160, 170, 180,
64, 75, 90, 100, 110, 120, 125, 128, 125, 128, 140, 150, 160, 170, 180, 190,
64, 75, 90, 100, 110, 120, 125, 128, 125, 128, 140, 150, 160, 170, 180, 190,
75, 90, 100, 110, 120, 125, 128, 140, 128, 140, 150, 160, 170, 180, 190, 200,
90, 100, 110, 120, 125, 128, 140, 150, 140, 150, 160, 170, 180, 190, 200, 210,
100, 110, 120, 125, 128, 140, 150, 160, 150, 160, 170, 180, 190, 200, 210, 220,
110, 120, 125, 128, 140, 150, 160, 170, 160, 170, 180, 190, 200, 210, 220, 230,
120, 125, 128, 140, 150, 160, 170, 180, 170, 180, 190, 200, 210, 220, 230, 240,
125, 128, 140, 150, 160, 170, 180, 190, 180, 190, 200, 210, 220, 230, 240, 250,
128, 140, 150, 160, 170, 180, 190, 200, 190, 200, 210, 220, 230, 240, 250, 255
), // Quality 3
intArrayOf(
16, 12, 10, 16, 24, 40, 51, 60, 51, 60, 72, 80, 88, 96, 100, 102,
11, 12, 14, 19, 26, 51, 60, 72, 60, 72, 80, 88, 96, 100, 102, 110,
14, 13, 16, 24, 40, 51, 60, 72, 60, 72, 80, 88, 96, 100, 102, 110,
14, 17, 22, 29, 51, 60, 72, 80, 72, 80, 88, 96, 100, 102, 110, 120,
18, 22, 37, 51, 60, 72, 80, 88, 80, 88, 96, 100, 102, 110, 120, 130,
24, 35, 51, 60, 72, 80, 88, 96, 88, 96, 100, 102, 110, 120, 130, 140,
49, 51, 60, 72, 80, 88, 96, 100, 96, 100, 102, 110, 120, 130, 140, 150,
51, 60, 72, 80, 88, 96, 100, 102, 100, 102, 110, 120, 130, 140, 150, 160,
51, 60, 72, 80, 88, 96, 100, 102, 100, 102, 110, 120, 130, 140, 150, 160,
60, 72, 80, 88, 96, 100, 102, 110, 102, 110, 120, 130, 140, 150, 160, 170,
72, 80, 88, 96, 100, 102, 110, 120, 110, 120, 130, 140, 150, 160, 170, 180,
80, 88, 96, 100, 102, 110, 120, 130, 120, 130, 140, 150, 160, 170, 180, 190,
88, 96, 100, 102, 110, 120, 130, 140, 130, 140, 150, 160, 170, 180, 190, 200,
96, 100, 102, 110, 120, 130, 140, 150, 140, 150, 160, 170, 180, 190, 200, 210,
100, 102, 110, 120, 130, 140, 150, 160, 150, 160, 170, 180, 190, 200, 210, 220,
102, 110, 120, 130, 140, 150, 160, 170, 160, 170, 180, 190, 200, 210, 220, 230
), // Quality 4
intArrayOf(
12, 9, 8, 12, 18, 30, 38, 45, 38, 45, 54, 60, 66, 72, 75, 77,
8, 9, 11, 14, 20, 38, 45, 54, 45, 54, 60, 66, 72, 75, 77, 85,
11, 10, 12, 18, 30, 38, 45, 54, 45, 54, 60, 66, 72, 75, 77, 85,
11, 13, 17, 22, 38, 45, 54, 60, 54, 60, 66, 72, 75, 77, 85, 95,
14, 17, 28, 38, 45, 54, 60, 66, 60, 66, 72, 75, 77, 85, 95, 105,
18, 26, 38, 45, 54, 60, 66, 72, 66, 72, 75, 77, 85, 95, 105, 115,
37, 38, 45, 54, 60, 66, 72, 75, 72, 75, 77, 85, 95, 105, 115, 125,
38, 45, 54, 60, 66, 72, 75, 77, 75, 77, 85, 95, 105, 115, 125, 135,
38, 45, 54, 60, 66, 72, 75, 77, 75, 77, 85, 95, 105, 115, 125, 135,
45, 54, 60, 66, 72, 75, 77, 85, 77, 85, 95, 105, 115, 125, 135, 145,
54, 60, 66, 72, 75, 77, 85, 95, 85, 95, 105, 115, 125, 135, 145, 155,
60, 66, 72, 75, 77, 85, 95, 105, 95, 105, 115, 125, 135, 145, 155, 165,
66, 72, 75, 77, 85, 95, 105, 115, 105, 115, 125, 135, 145, 155, 165, 175,
72, 75, 77, 85, 95, 105, 115, 125, 115, 125, 135, 145, 155, 165, 175, 185,
75, 77, 85, 95, 105, 115, 125, 135, 125, 135, 145, 155, 165, 175, 185, 195,
77, 85, 95, 105, 115, 125, 135, 145, 135, 145, 155, 165, 175, 185, 195, 205
), // Quality 5
intArrayOf(
10, 7, 6, 10, 15, 25, 32, 38, 32, 38, 45, 50, 55, 60, 63, 65,
7, 7, 9, 12, 16, 32, 38, 45, 38, 45, 50, 55, 60, 63, 65, 70,
9, 8, 10, 15, 25, 32, 38, 45, 38, 45, 50, 55, 60, 63, 65, 70,
9, 11, 14, 18, 32, 38, 45, 50, 45, 50, 55, 60, 63, 65, 70, 75,
12, 14, 23, 32, 38, 45, 50, 55, 50, 55, 60, 63, 65, 70, 75, 80,
15, 22, 32, 38, 45, 50, 55, 60, 55, 60, 63, 65, 70, 75, 80, 85,
31, 32, 38, 45, 50, 55, 60, 63, 60, 63, 65, 70, 75, 80, 85, 90,
32, 38, 45, 50, 55, 60, 63, 65, 63, 65, 70, 75, 80, 85, 90, 95,
32, 38, 45, 50, 55, 60, 63, 65, 63, 65, 70, 75, 80, 85, 90, 95,
38, 45, 50, 55, 60, 63, 65, 70, 65, 70, 75, 80, 85, 90, 95, 100,
45, 50, 55, 60, 63, 65, 70, 75, 70, 75, 80, 85, 90, 95, 100, 105,
50, 55, 60, 63, 65, 70, 75, 80, 75, 80, 85, 90, 95, 100, 105, 110,
55, 60, 63, 65, 70, 75, 80, 85, 80, 85, 90, 95, 100, 105, 110, 115,
60, 63, 65, 70, 75, 80, 85, 90, 85, 90, 95, 100, 105, 110, 115, 120,
63, 65, 70, 75, 80, 85, 90, 95, 90, 95, 100, 105, 110, 115, 120, 125,
65, 70, 75, 80, 85, 90, 95, 100, 95, 100, 105, 110, 115, 120, 125, 130
), // Quality 6
intArrayOf(
8, 6, 5, 8, 12, 20, 26, 30, 26, 30, 36, 40, 44, 48, 50, 52,
6, 6, 7, 10, 13, 26, 30, 36, 30, 36, 40, 44, 48, 50, 52, 56,
7, 7, 8, 12, 20, 26, 30, 36, 30, 36, 40, 44, 48, 50, 52, 56,
7, 9, 11, 15, 26, 30, 36, 40, 36, 40, 44, 48, 50, 52, 56, 60,
10, 11, 19, 26, 30, 36, 40, 44, 40, 44, 48, 50, 52, 56, 60, 64,
12, 17, 26, 30, 36, 40, 44, 48, 44, 48, 50, 52, 56, 60, 64, 68,
25, 26, 30, 36, 40, 44, 48, 50, 48, 50, 52, 56, 60, 64, 68, 72,
26, 30, 36, 40, 44, 48, 50, 52, 50, 52, 56, 60, 64, 68, 72, 76,
26, 30, 36, 40, 44, 48, 50, 52, 50, 52, 56, 60, 64, 68, 72, 76,
30, 36, 40, 44, 48, 50, 52, 56, 52, 56, 60, 64, 68, 72, 76, 80,
36, 40, 44, 48, 50, 52, 56, 60, 56, 60, 64, 68, 72, 76, 80, 84,
40, 44, 48, 50, 52, 56, 60, 64, 60, 64, 68, 72, 76, 80, 84, 88,
44, 48, 50, 52, 56, 60, 64, 68, 64, 68, 72, 76, 80, 84, 88, 92,
48, 50, 52, 56, 60, 64, 68, 72, 68, 72, 76, 80, 84, 88, 92, 96,
50, 52, 56, 60, 64, 68, 72, 76, 72, 76, 80, 84, 88, 92, 96, 100,
52, 56, 60, 64, 68, 72, 76, 80, 76, 80, 84, 88, 92, 96, 100, 104
), // Quality 7 (highest)
intArrayOf(
2, 1, 1, 2, 3, 5, 6, 7, 6, 7, 8, 9, 10, 11, 12, 13,
1, 1, 1, 2, 3, 6, 7, 9, 7, 9, 10, 11, 12, 13, 14, 15,
1, 1, 2, 3, 5, 6, 7, 9, 7, 9, 10, 11, 12, 13, 14, 15,
1, 2, 3, 4, 6, 7, 9, 10, 9, 10, 11, 12, 13, 14, 15, 16,
2, 3, 5, 6, 7, 9, 10, 11, 10, 11, 12, 13, 14, 15, 16, 17,
3, 4, 6, 7, 9, 10, 11, 12, 11, 12, 13, 14, 15, 16, 17, 18,
6, 6, 7, 9, 10, 11, 12, 13, 12, 13, 14, 15, 16, 17, 18, 19,
6, 7, 9, 10, 11, 12, 13, 14, 13, 14, 15, 16, 17, 18, 19, 20,
6, 7, 9, 10, 11, 12, 13, 14, 13, 14, 15, 16, 17, 18, 19, 20,
7, 9, 10, 11, 12, 13, 14, 15, 14, 15, 16, 17, 18, 19, 20, 21,
9, 10, 11, 12, 13, 14, 15, 16, 15, 16, 17, 18, 19, 20, 21, 22,
10, 11, 12, 13, 14, 15, 16, 17, 16, 17, 18, 19, 20, 21, 22, 23,
11, 12, 13, 14, 15, 16, 17, 18, 17, 18, 19, 20, 21, 22, 23, 24,
12, 13, 14, 15, 16, 17, 18, 19, 18, 19, 20, 21, 22, 23, 24, 25,
13, 14, 15, 16, 17, 18, 19, 20, 19, 20, 21, 22, 23, 24, 25, 26,
14, 15, 16, 17, 18, 19, 20, 21, 20, 21, 22, 23, 24, 25, 26, 27
)
)
val QUANT_TABLE_Y: IntArray = intArrayOf(
2, 1, 1, 2, 3, 5, 6, 7, 6, 7, 8, 9, 10, 11, 12, 13,
1, 1, 1, 2, 3, 6, 7, 9, 7, 9, 10, 11, 12, 13, 14, 15,
1, 1, 2, 3, 5, 6, 7, 9, 7, 9, 10, 11, 12, 13, 14, 15,
1, 2, 3, 4, 6, 7, 9, 10, 9, 10, 11, 12, 13, 14, 15, 16,
2, 3, 5, 6, 7, 9, 10, 11, 10, 11, 12, 13, 14, 15, 16, 17,
3, 4, 6, 7, 9, 10, 11, 12, 11, 12, 13, 14, 15, 16, 17, 18,
6, 6, 7, 9, 10, 11, 12, 13, 12, 13, 14, 15, 16, 17, 18, 19,
6, 7, 9, 10, 11, 12, 13, 14, 13, 14, 15, 16, 17, 18, 19, 20,
6, 7, 9, 10, 11, 12, 13, 14, 13, 14, 15, 16, 17, 18, 19, 20,
7, 9, 10, 11, 12, 13, 14, 15, 14, 15, 16, 17, 18, 19, 20, 21,
9, 10, 11, 12, 13, 14, 15, 16, 15, 16, 17, 18, 19, 20, 21, 22,
10, 11, 12, 13, 14, 15, 16, 17, 16, 17, 18, 19, 20, 21, 22, 23,
11, 12, 13, 14, 15, 16, 17, 18, 17, 18, 19, 20, 21, 22, 23, 24,
12, 13, 14, 15, 16, 17, 18, 19, 18, 19, 20, 21, 22, 23, 24, 25,
13, 14, 15, 16, 17, 18, 19, 20, 19, 20, 21, 22, 23, 24, 25, 26,
14, 15, 16, 17, 18, 19, 20, 21, 20, 21, 22, 23, 24, 25, 26, 27)
// Quality settings for quantization (Co channel - orange-blue, 8x8)
var QUANT_TABLES_CO: Array<IntArray> = arrayOf( // Quality 0 (lowest) - 2x more aggressive than Co
intArrayOf(
240, 180, 150, 240, 255, 255, 255, 255,
166, 180, 210, 255, 255, 255, 255, 255,
210, 196, 240, 255, 255, 255, 255, 255,
210, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255
), // Quality 1 - 1.8x more aggressive
intArrayOf(
108, 81, 68, 108, 162, 255, 255, 255,
76, 81, 95, 130, 176, 255, 255, 255,
95, 88, 108, 162, 255, 255, 255, 255,
95, 115, 149, 196, 255, 255, 255, 255,
122, 149, 250, 255, 255, 255, 255, 255,
162, 238, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255
), // Quality 2 - 1.7x more aggressive
intArrayOf(
51, 39, 32, 51, 77, 128, 163, 192,
36, 39, 46, 61, 83, 163, 192, 230,
46, 43, 51, 77, 128, 163, 192, 230,
46, 54, 71, 94, 163, 192, 230, 255,
58, 71, 119, 163, 192, 230, 255, 255,
77, 112, 163, 192, 230, 255, 255, 255,
158, 163, 192, 230, 255, 255, 255, 255,
163, 192, 230, 255, 255, 255, 255, 255
), // Quality 3 - 1.6x more aggressive
intArrayOf(
38, 29, 24, 38, 58, 96, 123, 144,
27, 29, 34, 46, 62, 123, 144, 173,
34, 32, 38, 58, 96, 123, 144, 173,
34, 42, 53, 70, 123, 144, 173, 192,
43, 53, 90, 123, 144, 173, 192, 211,
58, 85, 123, 144, 173, 192, 211, 230,
118, 123, 144, 173, 192, 211, 230, 240,
123, 144, 173, 192, 211, 230, 240, 246
), // Quality 4 - 1.5x more aggressive
intArrayOf(
27, 21, 18, 27, 41, 68, 86, 102,
20, 21, 24, 33, 45, 86, 102, 122,
24, 23, 27, 41, 68, 86, 102, 122,
24, 30, 38, 50, 86, 102, 122, 135,
30, 38, 63, 86, 102, 122, 135, 149,
41, 59, 86, 102, 122, 135, 149, 162,
84, 86, 102, 122, 135, 149, 162, 170,
86, 102, 122, 135, 149, 162, 170, 174
), // Quality 5 - 1.4x more aggressive
intArrayOf(
21, 15, 13, 21, 32, 53, 67, 80,
15, 15, 18, 25, 34, 67, 80, 95,
18, 17, 21, 32, 53, 67, 80, 95,
18, 22, 29, 39, 67, 80, 95, 105,
24, 29, 49, 67, 80, 95, 105, 116,
32, 46, 67, 80, 95, 105, 116, 126,
64, 67, 80, 95, 105, 116, 126, 132,
67, 80, 95, 105, 116, 126, 132, 134
), // Quality 6 - 1.3x more aggressive
intArrayOf(
16, 12, 10, 16, 23, 39, 51, 59,
12, 12, 14, 18, 26, 51, 59, 70,
14, 13, 16, 23, 39, 51, 59, 70,
14, 17, 22, 29, 51, 59, 70, 78,
18, 22, 36, 51, 59, 70, 78, 86,
23, 34, 51, 59, 70, 78, 86, 94,
49, 51, 59, 70, 78, 86, 94, 98,
51, 59, 70, 78, 86, 94, 98, 100
), // Quality 7 (highest) - 1.2x more aggressive for subtle improvement
intArrayOf(
1, 1, 1, 1, 1, 2, 2, 4,
1, 1, 1, 1, 2, 3, 4, 5,
1, 1, 1, 2, 3, 4, 5, 6,
1, 1, 2, 3, 4, 5, 6, 7,
1, 2, 3, 4, 5, 6, 7, 8,
2, 3, 4, 5, 6, 7, 8, 10,
3, 4, 5, 6, 7, 8, 10, 11,
4, 5, 6, 7, 8, 10, 11, 12
)
)
// Quality settings for quantization (Cg channel - green-magenta, much more aggressive than Co)
// Similar to NTSC Q channel reduction - exploit reduced human sensitivity to green-magenta
// Now using 3x-5x more aggressive quantization, similar to actual NTSC Q bandwidth reduction
var QUANT_TABLES_CG: Array<IntArray> = arrayOf( // Quality 0 (lowest) - 5x more aggressive than Co, maximum compression
intArrayOf(
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255
), // Quality 1 - 4.5x more aggressive, very low bandwidth
intArrayOf(
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255
), // Quality 2 - 4x more aggressive, preserve only DC and very low frequencies
intArrayOf(
120, 180, 240, 255, 255, 255, 255, 255,
180, 240, 255, 255, 255, 255, 255, 255,
240, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255
), // Quality 3 - 3.5x more aggressive, basic low frequency preservation
intArrayOf(
84, 108, 144, 192, 255, 255, 255, 255,
108, 144, 192, 255, 255, 255, 255, 255,
144, 192, 255, 255, 255, 255, 255, 255,
192, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255
), // Quality 4 - 3x more aggressive, moderate compression
intArrayOf(
54, 72, 96, 128, 180, 255, 255, 255,
72, 96, 128, 180, 255, 255, 255, 255,
96, 128, 180, 255, 255, 255, 255, 255,
128, 180, 255, 255, 255, 255, 255, 255,
180, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255
), // Quality 5 - 2.8x more aggressive, balanced compression
intArrayOf(
42, 56, 75, 100, 140, 200, 255, 255,
56, 75, 100, 140, 200, 255, 255, 255,
75, 100, 140, 200, 255, 255, 255, 255,
100, 140, 200, 255, 255, 255, 255, 255,
140, 200, 255, 255, 255, 255, 255, 255,
200, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255
), // Quality 6 - 2.5x more aggressive, good quality but still compressed
intArrayOf(
30, 40, 54, 72, 100, 144, 200, 255,
40, 54, 72, 100, 144, 200, 255, 255,
54, 72, 100, 144, 200, 255, 255, 255,
72, 100, 144, 200, 255, 255, 255, 255,
100, 144, 200, 255, 255, 255, 255, 255,
144, 200, 255, 255, 255, 255, 255, 255,
200, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255
), // Quality 7 (highest) - 2x more aggressive, preserve more detail
intArrayOf(
2, 3, 4, 6, 8, 12, 16, 20,
3, 4, 6, 8, 12, 16, 20, 24,
4, 6, 8, 12, 16, 20, 24, 28,
6, 8, 12, 16, 20, 24, 28, 32,
8, 12, 16, 20, 24, 28, 32, 36,
12, 16, 20, 24, 28, 32, 36, 40,
16, 20, 24, 28, 32, 36, 40, 44,
20, 24, 28, 32, 36, 40, 44, 48
)
)
val QUANT_TABLE_C: IntArray = intArrayOf(
2, 3, 4, 6, 8, 12, 16, 20,
3, 4, 6, 8, 12, 16, 20, 24,
4, 6, 8, 12, 16, 20, 24, 28,
6, 8, 12, 16, 20, 24, 28, 32,
8, 12, 16, 20, 24, 28, 32, 36,
12, 16, 20, 24, 28, 32, 36, 40,
16, 20, 24, 28, 32, 36, 40, 44,
20, 24, 28, 32, 36, 40, 44, 48)
/**
* Upload RGB frame buffer to graphics framebuffer with dithering
@@ -1856,10 +1571,14 @@ class GraphicsJSR223Delegate(private val vm: VM) {
val blocksX = (width + 15) / 16 // 16x16 blocks now
val blocksY = (height + 15) / 16
val quantTableY = QUANT_TABLES_Y[quality]
val quantTableCo = QUANT_TABLES_CO[quality]
val quantTableCg = QUANT_TABLES_CG[quality]
val quantYmult = QUANT_MULT_Y[quality]
val quantCOmult = QUANT_MULT_CO[quality]
val quantCGmult = QUANT_MULT_CG[quality]
val quantTableY = QUANT_TABLE_Y.map { it * quantYmult }.toIntArray()
val quantTableCo = QUANT_TABLE_C.map { it * quantCOmult }.toIntArray()
val quantTableCg = QUANT_TABLE_C.map { it * quantCGmult }.toIntArray()
var readPtr = blockDataPtr

299
video_encoder/encoder_tev.c
View File

@@ -33,127 +33,12 @@ static inline int CLAMP(int x, int min, int max) {
return x < min ? min : (x > max ? max : x);
}
static const int QUANT_MULT_Y[8] = {40, 20, 10, 8, 6, 5, 4, 1};
static const int QUANT_MULT_CO[8] = {40, 20, 10, 8, 6, 5, 4, 1};
static const int QUANT_MULT_CG[8] = {80, 40, 20, 16, 12, 10, 8, 2};
// Quality settings for quantization (Y channel) - 16x16 tables
static const uint8_t QUANT_TABLES_Y[8][256] = {
// Quality 0 (lowest) - 16x16 table
{80, 60, 50, 80, 120, 200, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
55, 60, 70, 95, 130, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
70, 65, 80, 120, 200, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
70, 85, 110, 145, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
90, 110, 185, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
120, 175, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
245, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255},
// Quality 1
{40, 30, 25, 40, 60, 100, 128, 150, 128, 150, 180, 200, 220, 240, 250, 255,
28, 30, 35, 48, 65, 128, 150, 180, 150, 180, 200, 220, 240, 250, 255, 255,
35, 33, 40, 60, 100, 128, 150, 180, 150, 180, 200, 220, 240, 250, 255, 255,
35, 43, 55, 73, 128, 150, 180, 200, 180, 200, 220, 240, 250, 255, 255, 255,
45, 55, 93, 128, 150, 180, 200, 220, 200, 220, 240, 250, 255, 255, 255, 255,
60, 88, 128, 150, 180, 200, 220, 240, 220, 240, 250, 255, 255, 255, 255, 255,
123, 128, 150, 180, 200, 220, 240, 250, 240, 250, 255, 255, 255, 255, 255, 255,
128, 150, 180, 200, 220, 240, 250, 255, 250, 255, 255, 255, 255, 255, 255, 255,
128, 150, 180, 200, 220, 240, 250, 255, 250, 255, 255, 255, 255, 255, 255, 255,
150, 180, 200, 220, 240, 250, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
180, 200, 220, 240, 250, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
200, 220, 240, 250, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
220, 240, 250, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
240, 250, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
250, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255},
// Quality 2
{20, 15, 13, 20, 30, 50, 64, 75, 64, 75, 90, 100, 110, 120, 125, 128,
14, 15, 18, 24, 33, 64, 75, 90, 75, 90, 100, 110, 120, 125, 128, 140,
18, 17, 20, 30, 50, 64, 75, 90, 75, 90, 100, 110, 120, 125, 128, 140,
18, 22, 28, 37, 64, 75, 90, 100, 90, 100, 110, 120, 125, 128, 140, 150,
23, 28, 47, 64, 75, 90, 100, 110, 100, 110, 120, 125, 128, 140, 150, 160,
30, 44, 64, 75, 90, 100, 110, 120, 110, 120, 125, 128, 140, 150, 160, 170,
62, 64, 75, 90, 100, 110, 120, 125, 120, 125, 128, 140, 150, 160, 170, 180,
64, 75, 90, 100, 110, 120, 125, 128, 125, 128, 140, 150, 160, 170, 180, 190,
64, 75, 90, 100, 110, 120, 125, 128, 125, 128, 140, 150, 160, 170, 180, 190,
75, 90, 100, 110, 120, 125, 128, 140, 128, 140, 150, 160, 170, 180, 190, 200,
90, 100, 110, 120, 125, 128, 140, 150, 140, 150, 160, 170, 180, 190, 200, 210,
100, 110, 120, 125, 128, 140, 150, 160, 150, 160, 170, 180, 190, 200, 210, 220,
110, 120, 125, 128, 140, 150, 160, 170, 160, 170, 180, 190, 200, 210, 220, 230,
120, 125, 128, 140, 150, 160, 170, 180, 170, 180, 190, 200, 210, 220, 230, 240,
125, 128, 140, 150, 160, 170, 180, 190, 180, 190, 200, 210, 220, 230, 240, 250,
128, 140, 150, 160, 170, 180, 190, 200, 190, 200, 210, 220, 230, 240, 250, 255},
// Quality 3
{16, 12, 10, 16, 24, 40, 51, 60, 51, 60, 72, 80, 88, 96, 100, 102,
11, 12, 14, 19, 26, 51, 60, 72, 60, 72, 80, 88, 96, 100, 102, 110,
14, 13, 16, 24, 40, 51, 60, 72, 60, 72, 80, 88, 96, 100, 102, 110,
14, 17, 22, 29, 51, 60, 72, 80, 72, 80, 88, 96, 100, 102, 110, 120,
18, 22, 37, 51, 60, 72, 80, 88, 80, 88, 96, 100, 102, 110, 120, 130,
24, 35, 51, 60, 72, 80, 88, 96, 88, 96, 100, 102, 110, 120, 130, 140,
49, 51, 60, 72, 80, 88, 96, 100, 96, 100, 102, 110, 120, 130, 140, 150,
51, 60, 72, 80, 88, 96, 100, 102, 100, 102, 110, 120, 130, 140, 150, 160,
51, 60, 72, 80, 88, 96, 100, 102, 100, 102, 110, 120, 130, 140, 150, 160,
60, 72, 80, 88, 96, 100, 102, 110, 102, 110, 120, 130, 140, 150, 160, 170,
72, 80, 88, 96, 100, 102, 110, 120, 110, 120, 130, 140, 150, 160, 170, 180,
80, 88, 96, 100, 102, 110, 120, 130, 120, 130, 140, 150, 160, 170, 180, 190,
88, 96, 100, 102, 110, 120, 130, 140, 130, 140, 150, 160, 170, 180, 190, 200,
96, 100, 102, 110, 120, 130, 140, 150, 140, 150, 160, 170, 180, 190, 200, 210,
100, 102, 110, 120, 130, 140, 150, 160, 150, 160, 170, 180, 190, 200, 210, 220,
102, 110, 120, 130, 140, 150, 160, 170, 160, 170, 180, 190, 200, 210, 220, 230},
// Quality 4
{12, 9, 8, 12, 18, 30, 38, 45, 38, 45, 54, 60, 66, 72, 75, 77,
8, 9, 11, 14, 20, 38, 45, 54, 45, 54, 60, 66, 72, 75, 77, 85,
11, 10, 12, 18, 30, 38, 45, 54, 45, 54, 60, 66, 72, 75, 77, 85,
11, 13, 17, 22, 38, 45, 54, 60, 54, 60, 66, 72, 75, 77, 85, 95,
14, 17, 28, 38, 45, 54, 60, 66, 60, 66, 72, 75, 77, 85, 95, 105,
18, 26, 38, 45, 54, 60, 66, 72, 66, 72, 75, 77, 85, 95, 105, 115,
37, 38, 45, 54, 60, 66, 72, 75, 72, 75, 77, 85, 95, 105, 115, 125,
38, 45, 54, 60, 66, 72, 75, 77, 75, 77, 85, 95, 105, 115, 125, 135,
38, 45, 54, 60, 66, 72, 75, 77, 75, 77, 85, 95, 105, 115, 125, 135,
45, 54, 60, 66, 72, 75, 77, 85, 77, 85, 95, 105, 115, 125, 135, 145,
54, 60, 66, 72, 75, 77, 85, 95, 85, 95, 105, 115, 125, 135, 145, 155,
60, 66, 72, 75, 77, 85, 95, 105, 95, 105, 115, 125, 135, 145, 155, 165,
66, 72, 75, 77, 85, 95, 105, 115, 105, 115, 125, 135, 145, 155, 165, 175,
72, 75, 77, 85, 95, 105, 115, 125, 115, 125, 135, 145, 155, 165, 175, 185,
75, 77, 85, 95, 105, 115, 125, 135, 125, 135, 145, 155, 165, 175, 185, 195,
77, 85, 95, 105, 115, 125, 135, 145, 135, 145, 155, 165, 175, 185, 195, 205},
// Quality 5
{10, 7, 6, 10, 15, 25, 32, 38, 32, 38, 45, 50, 55, 60, 63, 65,
7, 7, 9, 12, 16, 32, 38, 45, 38, 45, 50, 55, 60, 63, 65, 70,
9, 8, 10, 15, 25, 32, 38, 45, 38, 45, 50, 55, 60, 63, 65, 70,
9, 11, 14, 18, 32, 38, 45, 50, 45, 50, 55, 60, 63, 65, 70, 75,
12, 14, 23, 32, 38, 45, 50, 55, 50, 55, 60, 63, 65, 70, 75, 80,
15, 22, 32, 38, 45, 50, 55, 60, 55, 60, 63, 65, 70, 75, 80, 85,
31, 32, 38, 45, 50, 55, 60, 63, 60, 63, 65, 70, 75, 80, 85, 90,
32, 38, 45, 50, 55, 60, 63, 65, 63, 65, 70, 75, 80, 85, 90, 95,
32, 38, 45, 50, 55, 60, 63, 65, 63, 65, 70, 75, 80, 85, 90, 95,
38, 45, 50, 55, 60, 63, 65, 70, 65, 70, 75, 80, 85, 90, 95, 100,
45, 50, 55, 60, 63, 65, 70, 75, 70, 75, 80, 85, 90, 95, 100, 105,
50, 55, 60, 63, 65, 70, 75, 80, 75, 80, 85, 90, 95, 100, 105, 110,
55, 60, 63, 65, 70, 75, 80, 85, 80, 85, 90, 95, 100, 105, 110, 115,
60, 63, 65, 70, 75, 80, 85, 90, 85, 90, 95, 100, 105, 110, 115, 120,
63, 65, 70, 75, 80, 85, 90, 95, 90, 95, 100, 105, 110, 115, 120, 125,
65, 70, 75, 80, 85, 90, 95, 100, 95, 100, 105, 110, 115, 120, 125, 130},
// Quality 6
{8, 6, 5, 8, 12, 20, 26, 30, 26, 30, 36, 40, 44, 48, 50, 52,
6, 6, 7, 10, 13, 26, 30, 36, 30, 36, 40, 44, 48, 50, 52, 56,
7, 7, 8, 12, 20, 26, 30, 36, 30, 36, 40, 44, 48, 50, 52, 56,
7, 9, 11, 15, 26, 30, 36, 40, 36, 40, 44, 48, 50, 52, 56, 60,
10, 11, 19, 26, 30, 36, 40, 44, 40, 44, 48, 50, 52, 56, 60, 64,
12, 17, 26, 30, 36, 40, 44, 48, 44, 48, 50, 52, 56, 60, 64, 68,
25, 26, 30, 36, 40, 44, 48, 50, 48, 50, 52, 56, 60, 64, 68, 72,
26, 30, 36, 40, 44, 48, 50, 52, 50, 52, 56, 60, 64, 68, 72, 76,
26, 30, 36, 40, 44, 48, 50, 52, 50, 52, 56, 60, 64, 68, 72, 76,
30, 36, 40, 44, 48, 50, 52, 56, 52, 56, 60, 64, 68, 72, 76, 80,
36, 40, 44, 48, 50, 52, 56, 60, 56, 60, 64, 68, 72, 76, 80, 84,
40, 44, 48, 50, 52, 56, 60, 64, 60, 64, 68, 72, 76, 80, 84, 88,
44, 48, 50, 52, 56, 60, 64, 68, 64, 68, 72, 76, 80, 84, 88, 92,
48, 50, 52, 56, 60, 64, 68, 72, 68, 72, 76, 80, 84, 88, 92, 96,
50, 52, 56, 60, 64, 68, 72, 76, 72, 76, 80, 84, 88, 92, 96, 100,
52, 56, 60, 64, 68, 72, 76, 80, 76, 80, 84, 88, 92, 96, 100, 104},
static const uint32_t QUANT_TABLE_Y[256] =
// Quality 7 (highest)
{2, 1, 1, 2, 3, 5, 6, 7, 6, 7, 8, 9, 10, 11, 12, 13,
1, 1, 1, 2, 3, 6, 7, 9, 7, 9, 10, 11, 12, 13, 14, 15,
@@ -170,153 +55,10 @@ static const uint8_t QUANT_TABLES_Y[8][256] = {
11, 12, 13, 14, 15, 16, 17, 18, 17, 18, 19, 20, 21, 22, 23, 24,
12, 13, 14, 15, 16, 17, 18, 19, 18, 19, 20, 21, 22, 23, 24, 25,
13, 14, 15, 16, 17, 18, 19, 20, 19, 20, 21, 22, 23, 24, 25, 26,
14, 15, 16, 17, 18, 19, 20, 21, 20, 21, 22, 23, 24, 25, 26, 27}
};
14, 15, 16, 17, 18, 19, 20, 21, 20, 21, 22, 23, 24, 25, 26, 27};
// Quality settings for quantization (Co channel - 8x8)
static const uint8_t QUANT_TABLES_CO[8][64] = {
// Quality 0 (lowest) - 2x more aggressive than before
{240, 180, 150, 240, 255, 255, 255, 255,
166, 180, 210, 255, 255, 255, 255, 255,
210, 196, 240, 255, 255, 255, 255, 255,
210, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255},
// Quality 1 - 1.8x more aggressive
{108, 81, 68, 108, 162, 255, 255, 255,
76, 81, 95, 130, 176, 255, 255, 255,
95, 88, 108, 162, 255, 255, 255, 255,
95, 115, 149, 196, 255, 255, 255, 255,
122, 149, 250, 255, 255, 255, 255, 255,
162, 238, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255},
// Quality 2 - 1.7x more aggressive
{51, 39, 32, 51, 77, 128, 163, 192,
36, 39, 46, 61, 83, 163, 192, 230,
46, 43, 51, 77, 128, 163, 192, 230,
46, 54, 71, 94, 163, 192, 230, 255,
58, 71, 119, 163, 192, 230, 255, 255,
77, 112, 163, 192, 230, 255, 255, 255,
158, 163, 192, 230, 255, 255, 255, 255,
163, 192, 230, 255, 255, 255, 255, 255},
// Quality 3 - 1.6x more aggressive
{38, 29, 24, 38, 58, 96, 123, 144,
27, 29, 34, 46, 62, 123, 144, 173,
34, 32, 38, 58, 96, 123, 144, 173,
34, 42, 53, 70, 123, 144, 173, 192,
43, 53, 90, 123, 144, 173, 192, 211,
58, 85, 123, 144, 173, 192, 211, 230,
118, 123, 144, 173, 192, 211, 230, 240,
123, 144, 173, 192, 211, 230, 240, 246},
// Quality 4 - 1.5x more aggressive
{27, 21, 18, 27, 41, 68, 86, 102,
20, 21, 24, 33, 45, 86, 102, 122,
24, 23, 27, 41, 68, 86, 102, 122,
24, 30, 38, 50, 86, 102, 122, 135,
30, 38, 63, 86, 102, 122, 135, 149,
41, 59, 86, 102, 122, 135, 149, 162,
84, 86, 102, 122, 135, 149, 162, 170,
86, 102, 122, 135, 149, 162, 170, 174},
// Quality 5 - 1.4x more aggressive
{21, 15, 13, 21, 32, 53, 67, 80,
15, 15, 18, 25, 34, 67, 80, 95,
18, 17, 21, 32, 53, 67, 80, 95,
18, 22, 29, 39, 67, 80, 95, 105,
24, 29, 49, 67, 80, 95, 105, 116,
32, 46, 67, 80, 95, 105, 116, 126,
64, 67, 80, 95, 105, 116, 126, 132,
67, 80, 95, 105, 116, 126, 132, 134},
// Quality 6 - 1.3x more aggressive
{16, 12, 10, 16, 23, 39, 51, 59,
12, 12, 14, 18, 26, 51, 59, 70,
14, 13, 16, 23, 39, 51, 59, 70,
14, 17, 22, 29, 51, 59, 70, 78,
18, 22, 36, 51, 59, 70, 78, 86,
23, 34, 51, 59, 70, 78, 86, 94,
49, 51, 59, 70, 78, 86, 94, 98,
51, 59, 70, 78, 86, 94, 98, 100},
// Quality 7 (highest) - 1.2x more aggressive for subtle improvement
{1, 1, 1, 1, 1, 2, 2, 4,
1, 1, 1, 1, 2, 3, 4, 5,
1, 1, 1, 2, 3, 4, 5, 6,
1, 1, 2, 3, 4, 5, 6, 7,
1, 2, 3, 4, 5, 6, 7, 8,
2, 3, 4, 5, 6, 7, 8, 10,
3, 4, 5, 6, 7, 8, 10, 11,
4, 5, 6, 7, 8, 10, 11, 12}
};
// Quality settings for quantization (Cg channel - 8x8, much more aggressive than Co)
// Similar to NTSC Q channel reduction - exploit reduced human sensitivity to green-magenta
// Now using 3x-5x more aggressive quantization, similar to actual NTSC Q bandwidth reduction
static const uint8_t QUANT_TABLES_CG[8][64] = {
// Quality 0 (lowest) - 5x more aggressive than Co, maximum compression
{255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255},
// Quality 1 - 4.5x more aggressive, very low bandwidth
{255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255},
// Quality 2 - 4x more aggressive, preserve only DC and very low frequencies
{120, 180, 240, 255, 255, 255, 255, 255,
180, 240, 255, 255, 255, 255, 255, 255,
240, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255},
// Quality 3 - 3.5x more aggressive, basic low frequency preservation
{84, 108, 144, 192, 255, 255, 255, 255,
108, 144, 192, 255, 255, 255, 255, 255,
144, 192, 255, 255, 255, 255, 255, 255,
192, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255},
// Quality 4 - 3x more aggressive, moderate compression
{54, 72, 96, 128, 180, 255, 255, 255,
72, 96, 128, 180, 255, 255, 255, 255,
96, 128, 180, 255, 255, 255, 255, 255,
128, 180, 255, 255, 255, 255, 255, 255,
180, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255},
// Quality 5 - 2.8x more aggressive, balanced compression
{42, 56, 75, 100, 140, 200, 255, 255,
56, 75, 100, 140, 200, 255, 255, 255,
75, 100, 140, 200, 255, 255, 255, 255,
100, 140, 200, 255, 255, 255, 255, 255,
140, 200, 255, 255, 255, 255, 255, 255,
200, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255},
// Quality 6 - 2.5x more aggressive, good quality but still compressed
{30, 40, 54, 72, 100, 144, 200, 255,
40, 54, 72, 100, 144, 200, 255, 255,
54, 72, 100, 144, 200, 255, 255, 255,
72, 100, 144, 200, 255, 255, 255, 255,
100, 144, 200, 255, 255, 255, 255, 255,
144, 200, 255, 255, 255, 255, 255, 255,
200, 255, 255, 255, 255, 255, 255, 255,
255, 255, 255, 255, 255, 255, 255, 255},
// Quality 7 (highest) - 2x more aggressive, preserve more detail
static const uint32_t QUANT_TABLE_C[64] =
{2, 3, 4, 6, 8, 12, 16, 20,
3, 4, 6, 8, 12, 16, 20, 24,
4, 6, 8, 12, 16, 20, 24, 28,
@@ -324,8 +66,8 @@ static const uint8_t QUANT_TABLES_CG[8][64] = {
8, 12, 16, 20, 24, 28, 32, 36,
12, 16, 20, 24, 28, 32, 36, 40,
16, 20, 24, 28, 32, 36, 40, 44,
20, 24, 28, 32, 36, 40, 44, 48}
};
20, 24, 28, 32, 36, 40, 44, 48};
// Audio constants (reuse MP2 from existing system)
#define MP2_SAMPLE_RATE 32000
@@ -959,31 +701,34 @@ static void encode_block(tev_encoder_t *enc, int block_x, int block_y, int is_ke
}
}
// Apply fast DCT transform - 8x performance improvement
// Apply fast DCT transform
dct_16x16_fast(enc->y_workspace, enc->dct_workspace);
// Quantize Y coefficients (luma)
const uint8_t *y_quant = QUANT_TABLES_Y[enc->quality];
const uint32_t *y_quant = QUANT_TABLE_Y;
const uint32_t qmult_y = QUANT_MULT_Y[enc->quality];
for (int i = 0; i < 256; i++) {
block->y_coeffs[i] = quantize_coeff(enc->dct_workspace[i], y_quant[i], i == 0, 0);
block->y_coeffs[i] = quantize_coeff(enc->dct_workspace[i], y_quant[i] * qmult_y, i == 0, 0);
}
// Apply fast DCT transform to chroma - 4x performance improvement
// Apply fast DCT transform to chroma
dct_8x8_fast(enc->co_workspace, enc->dct_workspace);
// Quantize Co coefficients (chroma - orange-blue)
const uint8_t *co_quant = QUANT_TABLES_CO[enc->quality];
const uint32_t *co_quant = QUANT_TABLE_C;
const uint32_t qmult_co = QUANT_MULT_CO[enc->quality];
for (int i = 0; i < 64; i++) {
block->co_coeffs[i] = quantize_coeff(enc->dct_workspace[i], co_quant[i], i == 0, 1);
block->co_coeffs[i] = quantize_coeff(enc->dct_workspace[i], co_quant[i] * qmult_co, i == 0, 1);
}
// Apply fast DCT transform to Cg - 4x performance improvement
// Apply fast DCT transform to Cg
dct_8x8_fast(enc->cg_workspace, enc->dct_workspace);
// Quantize Cg coefficients (chroma - green-magenta, more aggressive like NTSC Q)
const uint8_t *cg_quant = QUANT_TABLES_CG[enc->quality];
// Quantize Cg coefficients (chroma - green-magenta, qmult_cg is more aggressive like NTSC Q)
const uint32_t *cg_quant = QUANT_TABLE_C;
const uint32_t qmult_cg = QUANT_MULT_CG[enc->quality];
for (int i = 0; i < 64; i++) {
block->cg_coeffs[i] = quantize_coeff(enc->dct_workspace[i], cg_quant[i], i == 0, 1);
block->cg_coeffs[i] = quantize_coeff(enc->dct_workspace[i], cg_quant[i] * qmult_cg, i == 0, 1);
}
// Set CBP (simplified - always encode all channels)