jpeg_encoder/
quantization.rs

1use alloc::boxed::Box;
2use core::num::NonZeroU16;
3
4/// # Quantization table used for encoding
5///
6/// Tables are based on tables from mozjpeg
7#[derive(Debug, Clone)]
8pub enum QuantizationTableType {
9    /// Sample quantization tables given in Annex K (Clause K.1) of Recommendation ITU-T T.81 (1992) | ISO/IEC 10918-1:1994.
10    Default,
11
12    /// Flat
13    Flat,
14
15    /// Custom, tuned for MS-SSIM
16    CustomMsSsim,
17
18    /// Custom, tuned for PSNR-HVS
19    CustomPsnrHvs,
20
21    /// ImageMagick table by N. Robidoux
22    ///
23    /// From <http://www.imagemagick.org/discourse-server/viewtopic.php?f=22&t=20333&p=98008#p98008>
24    ImageMagick,
25
26    /// Relevance of human vision to JPEG-DCT compression (1992) Klein, Silverstein and Carney.
27    KleinSilversteinCarney,
28
29    /// DCTune perceptual optimization of compressed dental X-Rays (1997) Watson, Taylor, Borthwick
30    DentalXRays,
31
32    /// A visual detection model for DCT coefficient quantization (12/9/93) Ahumada, Watson, Peterson
33    VisualDetectionModel,
34
35    /// An improved detection model for DCT coefficient quantization (1993) Peterson, Ahumada and Watson
36    ImprovedDetectionModel,
37
38    /// A user supplied quantization table
39    Custom(Box<[u16; 64]>),
40}
41
42impl QuantizationTableType {
43    fn index(&self) -> usize {
44        use QuantizationTableType::*;
45
46        match self {
47            Default => 0,
48            Flat => 1,
49            CustomMsSsim => 2,
50            CustomPsnrHvs => 3,
51            ImageMagick => 4,
52            KleinSilversteinCarney => 5,
53            DentalXRays => 6,
54            VisualDetectionModel => 7,
55            ImprovedDetectionModel => 8,
56            Custom(_) => panic!("Custom types not supported"),
57        }
58    }
59}
60
61// Tables are based on mozjpeg jcparam.c
62static DEFAULT_LUMA_TABLES: [[u16; 64]; 9] = [
63    [
64        // Annex K
65        16, 11, 10, 16, 24, 40, 51, 61, 12, 12, 14, 19, 26, 58, 60, 55, 14, 13, 16, 24, 40, 57, 69,
66        56, 14, 17, 22, 29, 51, 87, 80, 62, 18, 22, 37, 56, 68, 109, 103, 77, 24, 35, 55, 64, 81,
67        104, 113, 92, 49, 64, 78, 87, 103, 121, 120, 101, 72, 92, 95, 98, 112, 100, 103, 99,
68    ],
69    [
70        // Flat
71        16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16,
72        16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16,
73        16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16,
74    ],
75    [
76        // Custom, tuned for MS-SSIM
77        12, 17, 20, 21, 30, 34, 56, 63, 18, 20, 20, 26, 28, 51, 61, 55, 19, 20, 21, 26, 33, 58, 69,
78        55, 26, 26, 26, 30, 46, 87, 86, 66, 31, 33, 36, 40, 46, 96, 100, 73, 40, 35, 46, 62, 81,
79        100, 111, 91, 46, 66, 76, 86, 102, 121, 120, 101, 68, 90, 90, 96, 113, 102, 105, 103,
80    ],
81    [
82        // Custom, tuned for PSNR-HVS
83        9, 10, 12, 14, 27, 32, 51, 62, 11, 12, 14, 19, 27, 44, 59, 73, 12, 14, 18, 25, 42, 59, 79,
84        78, 17, 18, 25, 42, 61, 92, 87, 92, 23, 28, 42, 75, 79, 112, 112, 99, 40, 42, 59, 84, 88,
85        124, 132, 111, 42, 64, 78, 95, 105, 126, 125, 99, 70, 75, 100, 102, 116, 100, 107, 98,
86    ],
87    [
88        // ImageMagick table by N. Robidoux
89        // From http://www.imagemagick.org/discourse-server/viewtopic.php?f=22&t=20333&p=98008#p98008
90        16, 16, 16, 18, 25, 37, 56, 85, 16, 17, 20, 27, 34, 40, 53, 75, 16, 20, 24, 31, 43, 62, 91,
91        135, 18, 27, 31, 40, 53, 74, 106, 156, 25, 34, 43, 53, 69, 94, 131, 189, 37, 40, 62, 74,
92        94, 124, 169, 238, 56, 53, 91, 106, 131, 169, 226, 311, 85, 75, 135, 156, 189, 238, 311,
93        418,
94    ],
95    [
96        // Relevance of human vision to JPEG-DCT compression (1992) Klein, Silverstein and Carney.
97        10, 12, 14, 19, 26, 38, 57, 86, 12, 18, 21, 28, 35, 41, 54, 76, 14, 21, 25, 32, 44, 63, 92,
98        136, 19, 28, 32, 41, 54, 75, 107, 157, 26, 35, 44, 54, 70, 95, 132, 190, 38, 41, 63, 75,
99        95, 125, 170, 239, 57, 54, 92, 107, 132, 170, 227, 312, 86, 76, 136, 157, 190, 239, 312,
100        419,
101    ],
102    [
103        // DCTune perceptual optimization of compressed dental X-Rays (1997) Watson, Taylor, Borthwick
104        7, 8, 10, 14, 23, 44, 95, 241, 8, 8, 11, 15, 25, 47, 102, 255, 10, 11, 13, 19, 31, 58, 127,
105        255, 14, 15, 19, 27, 44, 83, 181, 255, 23, 25, 31, 44, 72, 136, 255, 255, 44, 47, 58, 83,
106        136, 255, 255, 255, 95, 102, 127, 181, 255, 255, 255, 255, 241, 255, 255, 255, 255, 255,
107        255, 255,
108    ],
109    [
110        // A visual detection model for DCT coefficient quantization (12/9/93) Ahumada, Watson, Peterson
111        15, 11, 11, 12, 15, 19, 25, 32, 11, 13, 10, 10, 12, 15, 19, 24, 11, 10, 14, 14, 16, 18, 22,
112        27, 12, 10, 14, 18, 21, 24, 28, 33, 15, 12, 16, 21, 26, 31, 36, 42, 19, 15, 18, 24, 31, 38,
113        45, 53, 25, 19, 22, 28, 36, 45, 55, 65, 32, 24, 27, 33, 42, 53, 65, 77,
114    ],
115    [
116        // An improved detection model for DCT coefficient quantization (1993) Peterson, Ahumada and Watson
117        14, 10, 11, 14, 19, 25, 34, 45, 10, 11, 11, 12, 15, 20, 26, 33, 11, 11, 15, 18, 21, 25, 31,
118        38, 14, 12, 18, 24, 28, 33, 39, 47, 19, 15, 21, 28, 36, 43, 51, 59, 25, 20, 25, 33, 43, 54,
119        64, 74, 34, 26, 31, 39, 51, 64, 77, 91, 45, 33, 38, 47, 59, 74, 91, 108,
120    ],
121];
122
123// Tables are based on mozjpeg jcparam.c
124static DEFAULT_CHROMA_TABLES: [[u16; 64]; 9] = [
125    [
126        // Annex K
127        17, 18, 24, 47, 99, 99, 99, 99, 18, 21, 26, 66, 99, 99, 99, 99, 24, 26, 56, 99, 99, 99, 99,
128        99, 47, 66, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99,
129        99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99,
130    ],
131    [
132        // Flat
133        16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16,
134        16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16,
135        16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16,
136    ],
137    [
138        // Custom, tuned for MS-SSIM
139        8, 12, 15, 15, 86, 96, 96, 98, 13, 13, 15, 26, 90, 96, 99, 98, 12, 15, 18, 96, 99, 99, 99,
140        99, 17, 16, 90, 96, 99, 99, 99, 99, 96, 96, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99,
141        99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99,
142    ],
143    [
144        //Custom, tuned for PSNR-HVS
145        9, 10, 17, 19, 62, 89, 91, 97, 12, 13, 18, 29, 84, 91, 88, 98, 14, 19, 29, 93, 95, 95, 98,
146        97, 20, 26, 84, 88, 95, 95, 98, 94, 26, 86, 91, 93, 97, 99, 98, 99, 99, 100, 98, 99, 99,
147        99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 97, 97, 99, 99, 99, 99, 97, 99,
148    ],
149    [
150        // ImageMagick table by N. Robidoux
151        // From http://www.imagemagick.org/discourse-server/viewtopic.php?f=22&t=20333&p=98008#p98008
152        16, 16, 16, 18, 25, 37, 56, 85, 16, 17, 20, 27, 34, 40, 53, 75, 16, 20, 24, 31, 43, 62, 91,
153        135, 18, 27, 31, 40, 53, 74, 106, 156, 25, 34, 43, 53, 69, 94, 131, 189, 37, 40, 62, 74,
154        94, 124, 169, 238, 56, 53, 91, 106, 131, 169, 226, 311, 85, 75, 135, 156, 189, 238, 311,
155        418,
156    ],
157    [
158        // Relevance of human vision to JPEG-DCT compression (1992) Klein, Silverstein and Carney.
159        10, 12, 14, 19, 26, 38, 57, 86, 12, 18, 21, 28, 35, 41, 54, 76, 14, 21, 25, 32, 44, 63, 92,
160        136, 19, 28, 32, 41, 54, 75, 107, 157, 26, 35, 44, 54, 70, 95, 132, 190, 38, 41, 63, 75,
161        95, 125, 170, 239, 57, 54, 92, 107, 132, 170, 227, 312, 86, 76, 136, 157, 190, 239, 312,
162        419,
163    ],
164    [
165        // DCTune perceptual optimization of compressed dental X-Rays (1997) Watson, Taylor, Borthwick
166        7, 8, 10, 14, 23, 44, 95, 241, 8, 8, 11, 15, 25, 47, 102, 255, 10, 11, 13, 19, 31, 58, 127,
167        255, 14, 15, 19, 27, 44, 83, 181, 255, 23, 25, 31, 44, 72, 136, 255, 255, 44, 47, 58, 83,
168        136, 255, 255, 255, 95, 102, 127, 181, 255, 255, 255, 255, 241, 255, 255, 255, 255, 255,
169        255, 255,
170    ],
171    [
172        // A visual detection model for DCT coefficient quantization (12/9/93) Ahumada, Watson, Peterson
173        15, 11, 11, 12, 15, 19, 25, 32, 11, 13, 10, 10, 12, 15, 19, 24, 11, 10, 14, 14, 16, 18, 22,
174        27, 12, 10, 14, 18, 21, 24, 28, 33, 15, 12, 16, 21, 26, 31, 36, 42, 19, 15, 18, 24, 31, 38,
175        45, 53, 25, 19, 22, 28, 36, 45, 55, 65, 32, 24, 27, 33, 42, 53, 65, 77,
176    ],
177    [
178        // An improved detection model for DCT coefficient quantization (1993) Peterson, Ahumada and Watson
179        14, 10, 11, 14, 19, 25, 34, 45, 10, 11, 11, 12, 15, 20, 26, 33, 11, 11, 15, 18, 21, 25, 31,
180        38, 14, 12, 18, 24, 28, 33, 39, 47, 19, 15, 21, 28, 36, 43, 51, 59, 25, 20, 25, 33, 43, 54,
181        64, 74, 34, 26, 31, 39, 51, 64, 77, 91, 45, 33, 38, 47, 59, 74, 91, 108,
182    ],
183];
184
185const SHIFT: u32 = 2 * 8 - 1;
186
187fn compute_reciprocal(divisor: u32) -> (i32, i32) {
188    if divisor <= 1 {
189        return (1, 0);
190    }
191
192    let mut reciprocals = (1 << SHIFT) / divisor;
193    let fractional = (1 << SHIFT) % divisor;
194
195    // Correction for rounding errors in division
196    let mut correction = divisor / 2;
197
198    if fractional != 0 {
199        if fractional <= correction {
200            correction += 1;
201        } else {
202            reciprocals += 1;
203        }
204    }
205
206    (reciprocals as i32, correction as i32)
207}
208
209pub struct QuantizationTable {
210    table: [NonZeroU16; 64],
211    reciprocals: [i32; 64],
212    corrections: [i32; 64],
213}
214
215impl QuantizationTable {
216    pub fn new_with_quality(
217        table: &QuantizationTableType,
218        quality: u8,
219        luma: bool,
220    ) -> QuantizationTable {
221        let table = match table {
222            QuantizationTableType::Custom(table) => Self::get_user_table(table),
223            table => {
224                let table = if luma {
225                    &DEFAULT_LUMA_TABLES[table.index()]
226                } else {
227                    &DEFAULT_CHROMA_TABLES[table.index()]
228                };
229                Self::get_with_quality(table, quality)
230            }
231        };
232
233        let mut reciprocals = [0i32; 64];
234        let mut corrections = [0i32; 64];
235
236        for i in 0..64 {
237            let (reciprocal, correction) = compute_reciprocal(table[i].get() as u32);
238
239            reciprocals[i] = reciprocal;
240            corrections[i] = correction;
241        }
242
243        QuantizationTable {
244            table,
245            reciprocals,
246            corrections,
247        }
248    }
249
250    fn get_user_table(table: &[u16; 64]) -> [NonZeroU16; 64] {
251        let mut q_table = [NonZeroU16::new(1).unwrap(); 64];
252        for (i, &v) in table.iter().enumerate() {
253            q_table[i] = match NonZeroU16::new(v.max(1).min(2 << 10) << 3) {
254                Some(v) => v,
255                None => panic!("Invalid quantization table value: {}", v),
256            };
257        }
258        q_table
259    }
260
261    fn get_with_quality(table: &[u16; 64], quality: u8) -> [NonZeroU16; 64] {
262        let quality = quality.max(1).min(100) as u32;
263
264        let scale = if quality < 50 {
265            5000 / quality
266        } else {
267            200 - quality * 2
268        };
269
270        let mut q_table = [NonZeroU16::new(1).unwrap(); 64];
271
272        for (i, &v) in table.iter().enumerate() {
273            let v = v as u32;
274
275            let v = (v * scale + 50) / 100;
276
277            let v = v.max(1).min(255) as u16;
278
279            // Table values are premultiplied with 8 because dct is scaled by 8
280            q_table[i] = NonZeroU16::new(v << 3).unwrap();
281        }
282        q_table
283    }
284
285    #[inline]
286    pub fn get(&self, index: usize) -> u8 {
287        (self.table[index].get() >> 3) as u8
288    }
289
290    #[inline]
291    pub fn quantize(&self, in_value: i16, index: usize) -> i16 {
292        let value = in_value as i32;
293
294        let reciprocal = self.reciprocals[index];
295        let corrections = self.corrections[index];
296
297        let abs_value = value.abs();
298
299        let mut product = (abs_value + corrections) * reciprocal;
300        product >>= SHIFT;
301
302        if value != abs_value {
303            product *= -1;
304        }
305
306        product as i16
307    }
308}
309
310#[cfg(test)]
311mod tests {
312    use crate::quantization::{QuantizationTable, QuantizationTableType};
313
314    #[test]
315    fn test_new_100() {
316        let q = QuantizationTable::new_with_quality(&QuantizationTableType::Default, 100, true);
317
318        for &v in &q.table {
319            let v = v.get();
320            assert_eq!(v, 1 << 3);
321        }
322
323        let q = QuantizationTable::new_with_quality(&QuantizationTableType::Default, 100, false);
324
325        for &v in &q.table {
326            let v = v.get();
327            assert_eq!(v, 1 << 3);
328        }
329    }
330
331    #[test]
332    fn test_new_100_quantize() {
333        let q = QuantizationTable::new_with_quality(&QuantizationTableType::Default, 100, true);
334
335        for i in -255..255 {
336            assert_eq!(i, q.quantize(i << 3, 0));
337        }
338    }
339}
jpeg_encoder/quantization.rs

jpeg_encoder/
quantization.rs
