Source: http://www.google.com/patents/US5539662?ie=ISO-8859-1
Timestamp: 2014-03-15 14:23:48
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Matched Legal Cases: ['art1', 'art2', 'art3', 'art4', 'art4', 'art3', 'art2', 'art1', 'art1', 'art2', 'art3', 'art4']

Patent US5539662 - Process, apparatus and system for transforming signals using strength ... - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inAdvanced Patent SearchPatentsThe complexity of a plurality of signals in a first domain are characterized. A transform is selected in accordance with the complexity of the plurality of signals, wherein the selected transform is one of a plurality of transforms having differing complexities. The selected transform is applied to the...http://www.google.com/patents/US5539662?utm_source=gb-gplus-sharePatent US5539662 - Process, apparatus and system for transforming signals using strength-reduced transformsAdvanced Patent SearchPublication numberUS5539662 APublication typeGrantApplication numberUS 08/234,324Publication dateJul 23, 1996Filing dateApr 28, 1994Priority dateNov 24, 1993Fee statusPaidPublication number08234324, 234324, US 5539662 A, US 5539662A, US-A-5539662, US5539662 A, US5539662AInventorsBrian NickersonOriginal AssigneeIntel CorporationExport CitationBiBTeX, EndNote, RefManPatent Citations (8), Referenced by (4), Classifications (101), Legal Events (5) External Links: USPTO, USPTO Assignment, EspacenetProcess, apparatus and system for transforming signals using strength-reduced transformsUS 5539662 AAbstract The complexity of a plurality of signals in a first domain are characterized. A transform is selected in accordance with the complexity of the plurality of signals, wherein the selected transform is one of a plurality of transforms having differing complexities. The selected transform is applied to the plurality of signals to generate a plurality of transformed signals in a second domain.
What is claimed is: 1. A computer-implemented process for transforming signals, comprising the steps of:(a) generating a complexity measure for a plurality of signals in a first domain: (b) selecting a transform in accordance with the complexity measure of the plurality of signals, wherein the selected transform is one of a plurality of transforms corresponding to differing values of the complexity measure; and (c) transforming the plurality of signals into a plurality of transformed signals in a second domain by applying the selected transform to the plurality of signals. 2. The process of claim 1, wherein:the plurality of signals in the first domain comprise a plurality of discrete slant transform coefficients in a spatial frequency domain arranged in a matrix; the plurality of discrete slant transform coefficients correspond to a region of a video image; the matrix comprises a plurality of columns and a plurality of rows; step (a) comprises the steps of:(1) generating the complexity measure for each column of the matrix; and (2) generating the complexity measure for each row of the matrix; step (b) comprises the steps of:(1) selecting one or more column transform operations in accordance with the complexity measures of the columns wherein the selected one or more column transform operations are one or more of a plurality of column transform operations corresponding to differing values of the complexity measure; and (2) selecting one or more row transform operations in accordance with the complexity measures of the columns, wherein the selected one or more row transform operations are one or more of a plurality of row transform operations corresponding to differing values of the complexity measure; and step (c) comprises the steps of applying the selected one or more column transform operations and the selected one or more row transform operations to the matrix to generate a plurality of component signals in a spatial domain, wherein the plurality of component signals correspond to the video image. 3. The process of claim 2, wherein:step (a) comprises the steps of:(1) generating a total column complexity mask for the plurality of columns of the matrix, wherein the total column complexity mask comprises a column complexity mask for each column of the plurality of columns; and (2) generating a row complexity mask for the plurality of columns of the matrix; and step (b) comprises the steps of:(1) selecting the one or more column transform operations in accordance with the total column complexity mask; and (2) selecting the one or more row transform operations in accordance with the row complexity mask. 4. The process of claim 2, wherein:the matrix comprises eight columns and eight rows; each column having discrete slant transform coefficients C.sub.0, C.sub.1, C.sub.2, C.sub.3, C.sub.4, C.sub.5, C.sub.6, and C.sub.7, from top to bottom; and the plurality of column transform operations corresponding to differing values of the complexity measure comprise:a first column transform operation corresponding to a column, wherein at least one of coefficients C.sub.4, C.sub.5, C.sub.6, and C.sub.7 is non-zero; a second column transform operation corresponding to a column, wherein all coefficients C.sub.4, C.sub.5, C.sub.6, and C.sub.7 are zero and at least one of coefficients C.sub.2, C.sub.3 is non-zero; a third column transform operation corresponding to a column, wherein all coefficients C.sub.2, C.sub.3, C.sub.4, C.sub.5, C.sub.6, and C.sub.7 are zero and coefficient C.sub.1 is non-zero; and a fourth column transform operation corresponding to a column, wherein all coefficients C.sub.1, C.sub.2, C.sub.3, C.sub.4, C.sub.5, C.sub.6, and C.sub.7 are zero and coefficient C.sub.0 is non-zero; and a fifth column transform operation corresponding to a column, wherein all coefficients C.sub.0, C.sub.1, C.sub.2, C.sub.3, C.sub.4, C.sub.5, C.sub.6, and C.sub.7 are zero. 5. An apparatus for transforming signals, comprising:(a) means for generating a complexity measure for a plurality of signals in a first domain; (b) means for selecting a transform in accordance with the complexity measure of the plurality of signals, wherein the selected transformed is one of a plurality of transforms corresponding to differing values of the complexity measure; and (c) means for transforming the plurality of signals into a plurality of transformed signals in a second domain by applying the selected transform to the plurality of signals. 6. The apparatus of claim 5, wherein:the plurality of signal in the first domain comprise a plurality of discrete slant transform coefficients in a spatial frequency domain arranged in a matrix; the plurality of discrete slant transform coefficients correspond to a region of a video image; the matrix comprises a plurality of columns and a plurality of rows; means (a) comprises:(1) means for generating the complexity measure for each column of the matrix; and (2) means for generating the complexity measure for each row of the matrix: means (b) comprises:(1) means for selecting one or more column transform operations in accordance with the complexity measures of the columns wherein the selected one or more column transform operations are one or more of a plurality of column transform operations corresponding to differing values of the complexity measure; and (2) means for selecting one or more row transform operations in accordance with the complexity measures of the columns, wherein the selected one or more row transform operations are one or more of a plurality of row transform operations corresponding to differing values of the complexity measure; and means (c) comprises means for applying the selected one or more column transform operations and the selected one or more row transform operations to the matrix to generate a plurality of component signals in a spatial domain, wherein the plurality of component signals correspond to the video image. 7. The apparatus of claim 6, wherein:means (a) comprises:(1) means for generating a total column complexity mask for the plurality of columns of the matrix, wherein the total column complexity mask comprises a column complexity mask for each column of the plurality of columns; and (2) means for generating a row complexity mask for the plurality of columns of the matrix; and means (b) comprises:(1) means for selecting the one or more column transform operations in accordance with the total column complexity mask; and (2) means for selecting the one or more row transform operations in accordance with the row complexity mask. 8. The apparatus of claim 6, wherein:the matrix comprises eight columns and eight rows; each column having discrete slant transform coefficients C.sub.0, C.sub.1, C.sub.2, C.sub.3, C.sub.4, C.sub.5, C.sub.6, and C.sub.7, from top to bottom; and the plurality of column transform operations corresponding to differing values of the complexity measure comprise:a first column transform operation corresponding to a column, wherein at least one of coefficients C.sub.4, C.sub.5, C.sub.6, and C.sub.7 is non-zero; a second column transform operation corresponding to a column, wherein all coefficients C.sub.4, C.sub.5, C.sub.6, and C.sub.7 are zero and at least one of coefficients C.sub.2, C.sub.3 is non-zero; a third column transform operation corresponding to a column, wherein all coefficients C.sub.2, C.sub.3, C.sub.4, C.sub.5, C.sub.6, and C.sub.7 are zero and coefficient C.sub.1 is non-zero; and a fourth column transform operation corresponding to a column, wherein all coefficients C.sub.1, C.sub.2, C.sub.3, C.sub.4, C.sub.5, C.sub.6, and C.sub.7 are zero and coefficient C.sub.0 is non-zero; and a fifth column transform operation corresponding to a column, wherein all coefficients C.sub.0, C.sub.1, C.sub.2, C.sub.3, C.sub.4, C.sub.5, C.sub.6, and C.sub.7 are zero. 9. The apparatus of claim 5, wherein the apparatus comprises a host processor.
10. A system for transforming signals, comprising:(a) a monitor; and (b) a conferencing system for:(1) generating a complexity measure for a plurality of signals in a first domain; (2) selecting a transform in accordance with the complexity measure of the plurality of signals, wherein the selected transform is one of a plurality of transforms corresponding to differing values of the complexity measure; (3) transforming the plurality of signals into a plurality of transformed signals in a second domain by applying the selected transform to the plurality of signals; and (4) transmitting a plurality of decoded signals corresponding to the plurality of transformed signal to the monitor for display. 11. The system of claim 10, wherein:the plurality of signals in the first domain comprise a plurality of discrete slant transform coefficients in a spatial frequency domain arranged in a matrix; the plurality of discrete slant transform coefficients correspond to a region of a video image; and the matrix comprises a plurality of columns and a plurality of rows; and the conferencing system:generates the complexity measure for each column of the matrix; generates the complexity measure for each row of the matrix; selects one or more column transform operations in accordance with the complexity measures of the columns wherein the selected one or more column transform operations are one or more of a plurality of column transform operations corresponding to differing values of the complexity measure; selects one or more row transform operations in accordance with the complexity measures of the columns, wherein the selected one or more row transform operations are one or more of a plurality of row transform operations corresponding to differing values of the complexity measure; and applies the selected one or more column transform operations and the selected one or more row transform operations to the matrix to generate a plurality of component signals in a spatial domain, wherein the plurality of component signals correspond to the video image. 12. The system of claim 11, wherein the conferencing system:generates a total column complexity mask for the plurality of columns of the matrix, wherein the total column complexity mask comprises a column complexity mask for each column of the plurality of columns; generates a row complexity mask for the plurality of columns of the matrix; selects the one or more column transform operations in accordance with the total column complexity mask; and selects the one or more row transform operations in accordance with the row complexity mask. 13. The system of claim 11, wherein:the matrix comprises eight columns and eight rows; each column having discrete slant transform coefficients C.sub.0, C.sub.1, C.sub.2, C.sub.3, C.sub.4, C.sub.5, C.sub.6, and C.sub.7, from top to bottom; and the plurality of column transform operations corresponding to differing values of the complexity measure comprise:a first column transform operation corresponding to a column, wherein at least one of coefficients C.sub.4, C.sub.5, C.sub.6, and C.sub.7 is non-zero; a second column transform operation corresponding to a column, wherein all coefficients C.sub.4, C.sub.5, C.sub.6, and C.sub.7 are zero and at least one of coefficients C.sub.2, C.sub.3 is non-zero; a third column transform operation corresponding to a column, wherein all coefficients C.sub.2, C.sub.3, C.sub.4, C.sub.5, C.sub.6, and C.sub.7 are zero and coefficient C.sub.1 is non-zero; and a fourth column transform operation corresponding to a column, wherein all coefficients C.sub.1, C.sub.2, C.sub.3, C.sub.4, C.sub.5, C.sub.6, and C.sub.7 are zero and coefficient C.sub.0 is non-zero; and a fifth column transform operation corresponding to a column, wherein all coefficients C.sub.0, C.sub.1, C.sub.2, C.sub.3, C.sub.4, C.sub.5, C.sub.6, and C.sub.7 are zero. 14. The system of claim 10, wherein the conferencing system comprises a host processor for applying the selected transform to transform the signals.
For uniform bit distribution over the macroblocks, the target number of bits for the current macroblock, B.sub.t (i) is preferably calculated as a specified target number of bits for the current component plane divided by the number of macroblocks in the current component plane. The specified target number of bits for the current component plane is a function of the transmission bandwidth, the number of frames per second, and the subsampling ratio for the component. For example, for video conferencing at 10 frames per second over ISDN lines with a transmission bandwidth of 90 Kbits/sec allocated for video. 9 Kbits are allocated per video frame. For YUV9 video signals with 16:1:1 YUV subsampling, the target numbers of bits per component plane are 8 Kbits for Y and 0.5 Kbits for U and V. The number of bits used B.sub.u (i-1) is preferably initialized to the target number of bits B.sub.t (i) at the beginning of the video stream. Bit distribution over the macroblocks may also be non-uniform.
Bit rate controller 1000 generates an estimate B.sub.u.sup.e (i-1) of the number of bits used to encode the previous macroblock i-1(in step 1004 of FIG. 10) using Equation (6) as follows: ##EQU4## where: K.sub.2 is a specified positive constant (preferably, 3);
C.sub.b.sup.a is the adjusted buffer content, which is used as the previous buffer content for the similar component plane of the next frame:
BPF=M.sub.intra.sup.q * IntraSAD+B.sub.intra.sup.q
BPF=M.sub.inter.sup.q * InterSAD+B.sub.inter.sup.q
BPF.sub.e =k*(M.sub.intra.sup.q * IntraSAD.sub.ave +B.sub.intra.sup.q)+(1-k)*(M.sub.inter.sup.q *InterSAD.sub.ave +B.sub.inter.sup.q)
As described above in reference to step 416 of FIG. 4, the encoder quantizes the DST coefficients. In a preferred embodiment, quantization is performed as follows: ##EQU6## where v.sub.u is the unquantized DST coefficient, q is the quantizer, "/" represents division with truncation, and v.sub.q is quantized DST coefficient. The different treatment of DST coefficients with negative values ensures truncation toward zero. Those skilled in the art will understand that a purpose of this is to improve compression by always truncating toward the smaller of the two nearest integer values.
TABLE IV______________________________________Image Sizes Indicated by the ImageSize Signal.ImageSizeValue         ImageSize______________________________________0             (160 1             (240 2             (320 3             defined______________________________________
______________________________________empty = 0            macroblockswhile (1)code = gethuff();           if (code &amp;lt; 42){empty += code; break;}else if (code == 42)empty += 41;    else if (code == 43)all macroblocks to end of slice are empty}______________________________________
Host processor 202 reconstructs the (8 coefficients using the runs of zero DST coefficients and the non-zero DST coefficient values to undo the zig-zag scanning sequence of FIG. 6 (step 2104). An (8 nay be created by the following procedure:
______________________________________for (i = 0; i &amp;lt; 8; i++)for (j = 0; j &amp;lt; 8; j++)coeff[i][j] = 0;start at position "-1` on the zig-zag path (one step "before" 0)for (each run/val pair)step forward by `run` positions on the zig-zag pathdeposit `val` at the new position}______________________________________
______________________________________for (i = 0; i &amp;lt; 8; i++)for (j = 0; j &amp;lt; 8; j++)q = Qmatrix[Intra][thisQ][i][j];c = coeff[i][j];if (c &amp;gt; 0)coeff[i][j] = (q * c) + (q &amp;gt;&amp;gt; 1) - (q &amp; 1);else if (c &amp;lt; 0)coeff[i][j] = (q * c) - (q &amp;gt;&amp;gt; 1) + (q &amp; 1);else if (c == 0)coeff[i][j] = 0;}______________________________________
______________________________________for (i = 0; i &amp;lt; 8; i++)for (j = 0; j &amp;lt; 8; j++)image[i][j] = clamp(MCprev[i][j]) + array[i][j], 8, 120);______________________________________
______________________________________for (i = 0; i &amp;lt; 8; i++)for (j = 0; j &amp;lt; 8; j++)image [i][j] = clamp (array [i][i], 8, 120);______________________________________
______________________________________k = 0;while (1)v = gethuff();if (v == EOB)break;else if (v == ESC) // get explicit run,val from bitstream{run[k] = gethuff() + 1;lo = gethuff();hi = gethuff();val[k] = tosigned((lo .linevert split. (hi &amp;lt;&amp;lt; 6)) + 1);}else // lookup run,val in tables{run[k] = runtbl[v];val[k] = valtbl[v];}k++}______________________________________
______________________________________slant8         // s = pointer to input column or row        // d = pointer to output column or rowint s[], d[], fwd;        // fwd = 1 for forward DST, 0 for        inverse DSTint r1, r2, r3, r4, r5, r6, r7, r8;int t, t1, *p;if (fwd)   // apply forward DST{p = s;r1 = *p++;   // store value pointed to by p to r1 and        // then increment pr2 = *p++;r3 = *p++;r4 = *p++;r5 = *p++;r6 = *p++;r7 = *p++;r8 = *p++;SlantPart1;SlantPart2;SlantPart3;SlantPart4;p = d;*p++ = r1;*p++ = r4;*p++ = r8;*p++ = r5;*p++ = r2;*p++ = r6;*p++ = r3;*p++ = r7;}else       // apply inverse DSTp = s;r1 = *p++;r4 = *p++;r8 = *p++;r5 = *p++;r2 = *p++;r6 = *p++;r3 = *p++;r7 = *p++;SlantPart4;SlantPart3;SlantPart2;SlantPart1;p = d;*p++ = r1;*p++ = r2;*P++ = r3;*p++ = r4;*p++ = r5;*p++ = r6;*p++ = r7;*p++ = r8;}}______________________________________
______________________________________#define SlantPart1bfly(r1, r4);bfly(r2, r3);bfly(r5, r8);bfly(r6, r7);#define SlantPart2bfly(r1, r2) ;reflect(r4, r3);bfly(r5, r6) ;reflect(r8, r7);#define SlantPart3bfly(r1, r5);bfly(r2, r6);bfly(r7, r3);bfly(r4, r8);#define SlantPart4t = r5 - (r5 &amp;gt;&amp;gt; 3) + (r4 &amp;gt;&amp;gt; 1); r4r5 = r4 - (r4 &amp;gt;&amp;gt; 3) - (r5 &amp;gt;&amp;gt; 1);r5r4 = t;______________________________________
______________________________________bfly(x, y):t = x + y;y = x - y;x = t;#define reflect(s1, s2)        t = s1 + (s1 &amp;gt;&amp;gt; 2) + (s1 &amp;gt;&amp;gt; 3) + (s2 &amp;gt;&amp;gt; 1) +(s2 &amp;gt;&amp;gt; 4);s2 = -s2 - (s2 &amp;gt;&amp;gt; 2) - (s2 &amp;gt;&amp;gt; 3) + (s1 &amp;gt;&amp;gt; 1) +(s1 &amp;gt;&amp;gt; 4);s1 = t;#define reflect(s1, s2)        t = s1 + (s1 &amp;gt;&amp;gt; 2) + (s2 &amp;gt;&amp;gt; 1)s2 = -s2 - (s2 &amp;gt;&amp;gt; 2) + (s1 &amp;gt;&amp;gt; 1);s1 = t;______________________________________
______________________________________for (i = 0; i &amp;lt; 8; i++)for (j = 0; j &amp;lt; 8; j++)array[i][j] = (array[i][j] + 4) &amp;gt;&amp;gt; 3______________________________________
______________________________________for (i = 0; i &amp;lt; 8; i++)for (j = 0; j &amp;lt; 8; j++)array[i][j] = array[i][j] &amp;gt;&amp;gt; 3______________________________________
TABLE IX______________________________________Initial Assignment of Column DST Operations and FinalAssignment of Row DST Operations.4-bitComplexity  Mask            DSTMask        Values          Operation______________________________________(1xxx)       8-15           slant8 (01xx)      4-7             slant4 (001x)      2-3             slant2 (0001)      1               slant1 (0000)      0               null______________________________________
q.sub.1 ≧T and if Block 1 is not {empty and inter and MV=0} or
B=(x+y)&amp;gt;&amp;gt;2
C=(y+z)&amp;gt;&amp;gt;2
______________________________________   add code length to bit pointer   loop while (bit pointer &amp;gt;= 8) {     increment byte pointer by 1;     decrement bit pointer by 8;     }______________________________________
______________________________________for (k = 0; k &amp;lt; 2; k++) // for each of inter, intra base matrices// Apply tilt to base matrixfor (j = 0; j &amp;lt; 8; j++)for (i = 0; i &amp;lt; 8; i++)Base [k][j ][i] = (Base [k][j][i] *       (32 + (i + j) * (Tilt[k] - 32)/32))/32;// Generate the 16 quantization matrices of this typefor (m = 0; m &amp;lt; 16; m++){for (j = 0; j &amp;lt; 8; j++){for (i = 0; i &amp;lt; 8; i++){   if (i == 0 &amp;&amp; j == 0 &amp;&amp; k == 1)     s = DCstep;   else     s = QuantStep;   q = (Base [k][j][i] *     (QuantStart + ((s*m) &amp;gt;&amp;gt; 2))) &amp;gt;&amp;gt; 6;   if (q &amp;lt; 2) q = 2;   if (q &amp;gt; 127) q = 127;   if (PowersOf2)     q = Round2[q];   else     q = q &amp;gt;&amp;gt; 1;   Qmatrix[k][m][j][i] = q;}}}}______________________________________
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