Index: third_party/libjpeg_turbo/jidctflt.c |
=================================================================== |
--- third_party/libjpeg_turbo/jidctflt.c (revision 0) |
+++ third_party/libjpeg_turbo/jidctflt.c (revision 0) |
@@ -0,0 +1,242 @@ |
+/* |
+ * jidctflt.c |
+ * |
+ * Copyright (C) 1994-1998, Thomas G. Lane. |
+ * This file is part of the Independent JPEG Group's software. |
+ * For conditions of distribution and use, see the accompanying README file. |
+ * |
+ * This file contains a floating-point implementation of the |
+ * inverse DCT (Discrete Cosine Transform). In the IJG code, this routine |
+ * must also perform dequantization of the input coefficients. |
+ * |
+ * This implementation should be more accurate than either of the integer |
+ * IDCT implementations. However, it may not give the same results on all |
+ * machines because of differences in roundoff behavior. Speed will depend |
+ * on the hardware's floating point capacity. |
+ * |
+ * A 2-D IDCT can be done by 1-D IDCT on each column followed by 1-D IDCT |
+ * on each row (or vice versa, but it's more convenient to emit a row at |
+ * a time). Direct algorithms are also available, but they are much more |
+ * complex and seem not to be any faster when reduced to code. |
+ * |
+ * This implementation is based on Arai, Agui, and Nakajima's algorithm for |
+ * scaled DCT. Their original paper (Trans. IEICE E-71(11):1095) is in |
+ * Japanese, but the algorithm is described in the Pennebaker & Mitchell |
+ * JPEG textbook (see REFERENCES section in file README). The following code |
+ * is based directly on figure 4-8 in P&M. |
+ * While an 8-point DCT cannot be done in less than 11 multiplies, it is |
+ * possible to arrange the computation so that many of the multiplies are |
+ * simple scalings of the final outputs. These multiplies can then be |
+ * folded into the multiplications or divisions by the JPEG quantization |
+ * table entries. The AA&N method leaves only 5 multiplies and 29 adds |
+ * to be done in the DCT itself. |
+ * The primary disadvantage of this method is that with a fixed-point |
+ * implementation, accuracy is lost due to imprecise representation of the |
+ * scaled quantization values. However, that problem does not arise if |
+ * we use floating point arithmetic. |
+ */ |
+ |
+#define JPEG_INTERNALS |
+#include "jinclude.h" |
+#include "jpeglib.h" |
+#include "jdct.h" /* Private declarations for DCT subsystem */ |
+ |
+#ifdef DCT_FLOAT_SUPPORTED |
+ |
+ |
+/* |
+ * This module is specialized to the case DCTSIZE = 8. |
+ */ |
+ |
+#if DCTSIZE != 8 |
+ Sorry, this code only copes with 8x8 DCTs. /* deliberate syntax err */ |
+#endif |
+ |
+ |
+/* Dequantize a coefficient by multiplying it by the multiplier-table |
+ * entry; produce a float result. |
+ */ |
+ |
+#define DEQUANTIZE(coef,quantval) (((FAST_FLOAT) (coef)) * (quantval)) |
+ |
+ |
+/* |
+ * Perform dequantization and inverse DCT on one block of coefficients. |
+ */ |
+ |
+GLOBAL(void) |
+jpeg_idct_float (j_decompress_ptr cinfo, jpeg_component_info * compptr, |
+ JCOEFPTR coef_block, |
+ JSAMPARRAY output_buf, JDIMENSION output_col) |
+{ |
+ FAST_FLOAT tmp0, tmp1, tmp2, tmp3, tmp4, tmp5, tmp6, tmp7; |
+ FAST_FLOAT tmp10, tmp11, tmp12, tmp13; |
+ FAST_FLOAT z5, z10, z11, z12, z13; |
+ JCOEFPTR inptr; |
+ FLOAT_MULT_TYPE * quantptr; |
+ FAST_FLOAT * wsptr; |
+ JSAMPROW outptr; |
+ JSAMPLE *range_limit = IDCT_range_limit(cinfo); |
+ int ctr; |
+ FAST_FLOAT workspace[DCTSIZE2]; /* buffers data between passes */ |
+ SHIFT_TEMPS |
+ |
+ /* Pass 1: process columns from input, store into work array. */ |
+ |
+ inptr = coef_block; |
+ quantptr = (FLOAT_MULT_TYPE *) compptr->dct_table; |
+ wsptr = workspace; |
+ for (ctr = DCTSIZE; ctr > 0; ctr--) { |
+ /* Due to quantization, we will usually find that many of the input |
+ * coefficients are zero, especially the AC terms. We can exploit this |
+ * by short-circuiting the IDCT calculation for any column in which all |
+ * the AC terms are zero. In that case each output is equal to the |
+ * DC coefficient (with scale factor as needed). |
+ * With typical images and quantization tables, half or more of the |
+ * column DCT calculations can be simplified this way. |
+ */ |
+ |
+ if (inptr[DCTSIZE*1] == 0 && inptr[DCTSIZE*2] == 0 && |
+ inptr[DCTSIZE*3] == 0 && inptr[DCTSIZE*4] == 0 && |
+ inptr[DCTSIZE*5] == 0 && inptr[DCTSIZE*6] == 0 && |
+ inptr[DCTSIZE*7] == 0) { |
+ /* AC terms all zero */ |
+ FAST_FLOAT dcval = DEQUANTIZE(inptr[DCTSIZE*0], quantptr[DCTSIZE*0]); |
+ |
+ wsptr[DCTSIZE*0] = dcval; |
+ wsptr[DCTSIZE*1] = dcval; |
+ wsptr[DCTSIZE*2] = dcval; |
+ wsptr[DCTSIZE*3] = dcval; |
+ wsptr[DCTSIZE*4] = dcval; |
+ wsptr[DCTSIZE*5] = dcval; |
+ wsptr[DCTSIZE*6] = dcval; |
+ wsptr[DCTSIZE*7] = dcval; |
+ |
+ inptr++; /* advance pointers to next column */ |
+ quantptr++; |
+ wsptr++; |
+ continue; |
+ } |
+ |
+ /* Even part */ |
+ |
+ tmp0 = DEQUANTIZE(inptr[DCTSIZE*0], quantptr[DCTSIZE*0]); |
+ tmp1 = DEQUANTIZE(inptr[DCTSIZE*2], quantptr[DCTSIZE*2]); |
+ tmp2 = DEQUANTIZE(inptr[DCTSIZE*4], quantptr[DCTSIZE*4]); |
+ tmp3 = DEQUANTIZE(inptr[DCTSIZE*6], quantptr[DCTSIZE*6]); |
+ |
+ tmp10 = tmp0 + tmp2; /* phase 3 */ |
+ tmp11 = tmp0 - tmp2; |
+ |
+ tmp13 = tmp1 + tmp3; /* phases 5-3 */ |
+ tmp12 = (tmp1 - tmp3) * ((FAST_FLOAT) 1.414213562) - tmp13; /* 2*c4 */ |
+ |
+ tmp0 = tmp10 + tmp13; /* phase 2 */ |
+ tmp3 = tmp10 - tmp13; |
+ tmp1 = tmp11 + tmp12; |
+ tmp2 = tmp11 - tmp12; |
+ |
+ /* Odd part */ |
+ |
+ tmp4 = DEQUANTIZE(inptr[DCTSIZE*1], quantptr[DCTSIZE*1]); |
+ tmp5 = DEQUANTIZE(inptr[DCTSIZE*3], quantptr[DCTSIZE*3]); |
+ tmp6 = DEQUANTIZE(inptr[DCTSIZE*5], quantptr[DCTSIZE*5]); |
+ tmp7 = DEQUANTIZE(inptr[DCTSIZE*7], quantptr[DCTSIZE*7]); |
+ |
+ z13 = tmp6 + tmp5; /* phase 6 */ |
+ z10 = tmp6 - tmp5; |
+ z11 = tmp4 + tmp7; |
+ z12 = tmp4 - tmp7; |
+ |
+ tmp7 = z11 + z13; /* phase 5 */ |
+ tmp11 = (z11 - z13) * ((FAST_FLOAT) 1.414213562); /* 2*c4 */ |
+ |
+ z5 = (z10 + z12) * ((FAST_FLOAT) 1.847759065); /* 2*c2 */ |
+ tmp10 = ((FAST_FLOAT) 1.082392200) * z12 - z5; /* 2*(c2-c6) */ |
+ tmp12 = ((FAST_FLOAT) -2.613125930) * z10 + z5; /* -2*(c2+c6) */ |
+ |
+ tmp6 = tmp12 - tmp7; /* phase 2 */ |
+ tmp5 = tmp11 - tmp6; |
+ tmp4 = tmp10 + tmp5; |
+ |
+ wsptr[DCTSIZE*0] = tmp0 + tmp7; |
+ wsptr[DCTSIZE*7] = tmp0 - tmp7; |
+ wsptr[DCTSIZE*1] = tmp1 + tmp6; |
+ wsptr[DCTSIZE*6] = tmp1 - tmp6; |
+ wsptr[DCTSIZE*2] = tmp2 + tmp5; |
+ wsptr[DCTSIZE*5] = tmp2 - tmp5; |
+ wsptr[DCTSIZE*4] = tmp3 + tmp4; |
+ wsptr[DCTSIZE*3] = tmp3 - tmp4; |
+ |
+ inptr++; /* advance pointers to next column */ |
+ quantptr++; |
+ wsptr++; |
+ } |
+ |
+ /* Pass 2: process rows from work array, store into output array. */ |
+ /* Note that we must descale the results by a factor of 8 == 2**3. */ |
+ |
+ wsptr = workspace; |
+ for (ctr = 0; ctr < DCTSIZE; ctr++) { |
+ outptr = output_buf[ctr] + output_col; |
+ /* Rows of zeroes can be exploited in the same way as we did with columns. |
+ * However, the column calculation has created many nonzero AC terms, so |
+ * the simplification applies less often (typically 5% to 10% of the time). |
+ * And testing floats for zero is relatively expensive, so we don't bother. |
+ */ |
+ |
+ /* Even part */ |
+ |
+ tmp10 = wsptr[0] + wsptr[4]; |
+ tmp11 = wsptr[0] - wsptr[4]; |
+ |
+ tmp13 = wsptr[2] + wsptr[6]; |
+ tmp12 = (wsptr[2] - wsptr[6]) * ((FAST_FLOAT) 1.414213562) - tmp13; |
+ |
+ tmp0 = tmp10 + tmp13; |
+ tmp3 = tmp10 - tmp13; |
+ tmp1 = tmp11 + tmp12; |
+ tmp2 = tmp11 - tmp12; |
+ |
+ /* Odd part */ |
+ |
+ z13 = wsptr[5] + wsptr[3]; |
+ z10 = wsptr[5] - wsptr[3]; |
+ z11 = wsptr[1] + wsptr[7]; |
+ z12 = wsptr[1] - wsptr[7]; |
+ |
+ tmp7 = z11 + z13; |
+ tmp11 = (z11 - z13) * ((FAST_FLOAT) 1.414213562); |
+ |
+ z5 = (z10 + z12) * ((FAST_FLOAT) 1.847759065); /* 2*c2 */ |
+ tmp10 = ((FAST_FLOAT) 1.082392200) * z12 - z5; /* 2*(c2-c6) */ |
+ tmp12 = ((FAST_FLOAT) -2.613125930) * z10 + z5; /* -2*(c2+c6) */ |
+ |
+ tmp6 = tmp12 - tmp7; |
+ tmp5 = tmp11 - tmp6; |
+ tmp4 = tmp10 + tmp5; |
+ |
+ /* Final output stage: scale down by a factor of 8 and range-limit */ |
+ |
+ outptr[0] = range_limit[(int) DESCALE((INT32) (tmp0 + tmp7), 3) |
+ & RANGE_MASK]; |
+ outptr[7] = range_limit[(int) DESCALE((INT32) (tmp0 - tmp7), 3) |
+ & RANGE_MASK]; |
+ outptr[1] = range_limit[(int) DESCALE((INT32) (tmp1 + tmp6), 3) |
+ & RANGE_MASK]; |
+ outptr[6] = range_limit[(int) DESCALE((INT32) (tmp1 - tmp6), 3) |
+ & RANGE_MASK]; |
+ outptr[2] = range_limit[(int) DESCALE((INT32) (tmp2 + tmp5), 3) |
+ & RANGE_MASK]; |
+ outptr[5] = range_limit[(int) DESCALE((INT32) (tmp2 - tmp5), 3) |
+ & RANGE_MASK]; |
+ outptr[4] = range_limit[(int) DESCALE((INT32) (tmp3 + tmp4), 3) |
+ & RANGE_MASK]; |
+ outptr[3] = range_limit[(int) DESCALE((INT32) (tmp3 - tmp4), 3) |
+ & RANGE_MASK]; |
+ |
+ wsptr += DCTSIZE; /* advance pointer to next row */ |
+ } |
+} |
+ |
+#endif /* DCT_FLOAT_SUPPORTED */ |