4 * This file was part of the Independent JPEG Group's software:
5 * Copyright (C) 1994-1998, Thomas G. Lane.
6 * Modified 2010 by Guido Vollbeding.
7 * libjpeg-turbo Modifications:
8 * Copyright (C) 2014, D. R. Commander.
9 * For conditions of distribution and use, see the accompanying README file.
11 * This file contains a floating-point implementation of the
12 * inverse DCT (Discrete Cosine Transform). In the IJG code, this routine
13 * must also perform dequantization of the input coefficients.
15 * This implementation should be more accurate than either of the integer
16 * IDCT implementations. However, it may not give the same results on all
17 * machines because of differences in roundoff behavior. Speed will depend
18 * on the hardware's floating point capacity.
20 * A 2-D IDCT can be done by 1-D IDCT on each column followed by 1-D IDCT
21 * on each row (or vice versa, but it's more convenient to emit a row at
22 * a time). Direct algorithms are also available, but they are much more
23 * complex and seem not to be any faster when reduced to code.
25 * This implementation is based on Arai, Agui, and Nakajima's algorithm for
26 * scaled DCT. Their original paper (Trans. IEICE E-71(11):1095) is in
27 * Japanese, but the algorithm is described in the Pennebaker & Mitchell
28 * JPEG textbook (see REFERENCES section in file README). The following code
29 * is based directly on figure 4-8 in P&M.
30 * While an 8-point DCT cannot be done in less than 11 multiplies, it is
31 * possible to arrange the computation so that many of the multiplies are
32 * simple scalings of the final outputs. These multiplies can then be
33 * folded into the multiplications or divisions by the JPEG quantization
34 * table entries. The AA&N method leaves only 5 multiplies and 29 adds
35 * to be done in the DCT itself.
36 * The primary disadvantage of this method is that with a fixed-point
37 * implementation, accuracy is lost due to imprecise representation of the
38 * scaled quantization values. However, that problem does not arise if
39 * we use floating point arithmetic.
42 #define JPEG_INTERNALS
45 #include "jdct.h" /* Private declarations for DCT subsystem */
47 #ifdef DCT_FLOAT_SUPPORTED
51 * This module is specialized to the case DCTSIZE = 8.
55 Sorry, this code only copes with 8x8 DCTs. /* deliberate syntax err */
59 /* Dequantize a coefficient by multiplying it by the multiplier-table
60 * entry; produce a float result.
63 #define DEQUANTIZE(coef,quantval) (((FAST_FLOAT) (coef)) * (quantval))
67 * Perform dequantization and inverse DCT on one block of coefficients.
71 jpeg_idct_float (j_decompress_ptr cinfo, jpeg_component_info * compptr,
73 JSAMPARRAY output_buf, JDIMENSION output_col)
75 FAST_FLOAT tmp0, tmp1, tmp2, tmp3, tmp4, tmp5, tmp6, tmp7;
76 FAST_FLOAT tmp10, tmp11, tmp12, tmp13;
77 FAST_FLOAT z5, z10, z11, z12, z13;
79 FLOAT_MULT_TYPE * quantptr;
82 JSAMPLE *range_limit = cinfo->sample_range_limit;
84 FAST_FLOAT workspace[DCTSIZE2]; /* buffers data between passes */
85 #define _0_125 ((FLOAT_MULT_TYPE)0.125)
87 /* Pass 1: process columns from input, store into work array. */
90 quantptr = (FLOAT_MULT_TYPE *) compptr->dct_table;
92 for (ctr = DCTSIZE; ctr > 0; ctr--) {
93 /* Due to quantization, we will usually find that many of the input
94 * coefficients are zero, especially the AC terms. We can exploit this
95 * by short-circuiting the IDCT calculation for any column in which all
96 * the AC terms are zero. In that case each output is equal to the
97 * DC coefficient (with scale factor as needed).
98 * With typical images and quantization tables, half or more of the
99 * column DCT calculations can be simplified this way.
102 if (inptr[DCTSIZE*1] == 0 && inptr[DCTSIZE*2] == 0 &&
103 inptr[DCTSIZE*3] == 0 && inptr[DCTSIZE*4] == 0 &&
104 inptr[DCTSIZE*5] == 0 && inptr[DCTSIZE*6] == 0 &&
105 inptr[DCTSIZE*7] == 0) {
106 /* AC terms all zero */
107 FAST_FLOAT dcval = DEQUANTIZE(inptr[DCTSIZE*0],
108 quantptr[DCTSIZE*0] * _0_125);
110 wsptr[DCTSIZE*0] = dcval;
111 wsptr[DCTSIZE*1] = dcval;
112 wsptr[DCTSIZE*2] = dcval;
113 wsptr[DCTSIZE*3] = dcval;
114 wsptr[DCTSIZE*4] = dcval;
115 wsptr[DCTSIZE*5] = dcval;
116 wsptr[DCTSIZE*6] = dcval;
117 wsptr[DCTSIZE*7] = dcval;
119 inptr++; /* advance pointers to next column */
127 tmp0 = DEQUANTIZE(inptr[DCTSIZE*0], quantptr[DCTSIZE*0] * _0_125);
128 tmp1 = DEQUANTIZE(inptr[DCTSIZE*2], quantptr[DCTSIZE*2] * _0_125);
129 tmp2 = DEQUANTIZE(inptr[DCTSIZE*4], quantptr[DCTSIZE*4] * _0_125);
130 tmp3 = DEQUANTIZE(inptr[DCTSIZE*6], quantptr[DCTSIZE*6] * _0_125);
132 tmp10 = tmp0 + tmp2; /* phase 3 */
135 tmp13 = tmp1 + tmp3; /* phases 5-3 */
136 tmp12 = (tmp1 - tmp3) * ((FAST_FLOAT) 1.414213562) - tmp13; /* 2*c4 */
138 tmp0 = tmp10 + tmp13; /* phase 2 */
139 tmp3 = tmp10 - tmp13;
140 tmp1 = tmp11 + tmp12;
141 tmp2 = tmp11 - tmp12;
145 tmp4 = DEQUANTIZE(inptr[DCTSIZE*1], quantptr[DCTSIZE*1] * _0_125);
146 tmp5 = DEQUANTIZE(inptr[DCTSIZE*3], quantptr[DCTSIZE*3] * _0_125);
147 tmp6 = DEQUANTIZE(inptr[DCTSIZE*5], quantptr[DCTSIZE*5] * _0_125);
148 tmp7 = DEQUANTIZE(inptr[DCTSIZE*7], quantptr[DCTSIZE*7] * _0_125);
150 z13 = tmp6 + tmp5; /* phase 6 */
155 tmp7 = z11 + z13; /* phase 5 */
156 tmp11 = (z11 - z13) * ((FAST_FLOAT) 1.414213562); /* 2*c4 */
158 z5 = (z10 + z12) * ((FAST_FLOAT) 1.847759065); /* 2*c2 */
159 tmp10 = z5 - z12 * ((FAST_FLOAT) 1.082392200); /* 2*(c2-c6) */
160 tmp12 = z5 - z10 * ((FAST_FLOAT) 2.613125930); /* 2*(c2+c6) */
162 tmp6 = tmp12 - tmp7; /* phase 2 */
166 wsptr[DCTSIZE*0] = tmp0 + tmp7;
167 wsptr[DCTSIZE*7] = tmp0 - tmp7;
168 wsptr[DCTSIZE*1] = tmp1 + tmp6;
169 wsptr[DCTSIZE*6] = tmp1 - tmp6;
170 wsptr[DCTSIZE*2] = tmp2 + tmp5;
171 wsptr[DCTSIZE*5] = tmp2 - tmp5;
172 wsptr[DCTSIZE*3] = tmp3 + tmp4;
173 wsptr[DCTSIZE*4] = tmp3 - tmp4;
175 inptr++; /* advance pointers to next column */
180 /* Pass 2: process rows from work array, store into output array. */
183 for (ctr = 0; ctr < DCTSIZE; ctr++) {
184 outptr = output_buf[ctr] + output_col;
185 /* Rows of zeroes can be exploited in the same way as we did with columns.
186 * However, the column calculation has created many nonzero AC terms, so
187 * the simplification applies less often (typically 5% to 10% of the time).
188 * And testing floats for zero is relatively expensive, so we don't bother.
193 /* Apply signed->unsigned and prepare float->int conversion */
194 z5 = wsptr[0] + ((FAST_FLOAT) CENTERJSAMPLE + (FAST_FLOAT) 0.5);
195 tmp10 = z5 + wsptr[4];
196 tmp11 = z5 - wsptr[4];
198 tmp13 = wsptr[2] + wsptr[6];
199 tmp12 = (wsptr[2] - wsptr[6]) * ((FAST_FLOAT) 1.414213562) - tmp13;
201 tmp0 = tmp10 + tmp13;
202 tmp3 = tmp10 - tmp13;
203 tmp1 = tmp11 + tmp12;
204 tmp2 = tmp11 - tmp12;
208 z13 = wsptr[5] + wsptr[3];
209 z10 = wsptr[5] - wsptr[3];
210 z11 = wsptr[1] + wsptr[7];
211 z12 = wsptr[1] - wsptr[7];
214 tmp11 = (z11 - z13) * ((FAST_FLOAT) 1.414213562);
216 z5 = (z10 + z12) * ((FAST_FLOAT) 1.847759065); /* 2*c2 */
217 tmp10 = z5 - z12 * ((FAST_FLOAT) 1.082392200); /* 2*(c2-c6) */
218 tmp12 = z5 - z10 * ((FAST_FLOAT) 2.613125930); /* 2*(c2+c6) */
224 /* Final output stage: float->int conversion and range-limit */
226 outptr[0] = range_limit[((int) (tmp0 + tmp7)) & RANGE_MASK];
227 outptr[7] = range_limit[((int) (tmp0 - tmp7)) & RANGE_MASK];
228 outptr[1] = range_limit[((int) (tmp1 + tmp6)) & RANGE_MASK];
229 outptr[6] = range_limit[((int) (tmp1 - tmp6)) & RANGE_MASK];
230 outptr[2] = range_limit[((int) (tmp2 + tmp5)) & RANGE_MASK];
231 outptr[5] = range_limit[((int) (tmp2 - tmp5)) & RANGE_MASK];
232 outptr[3] = range_limit[((int) (tmp3 + tmp4)) & RANGE_MASK];
233 outptr[4] = range_limit[((int) (tmp3 - tmp4)) & RANGE_MASK];
235 wsptr += DCTSIZE; /* advance pointer to next row */
239 #endif /* DCT_FLOAT_SUPPORTED */