CN108282662B - Optimization method and device for continuous tone static image compression - Google Patents
Optimization method and device for continuous tone static image compression Download PDFInfo
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Abstract
The invention relates to an optimization method and a device for continuous tone static image compression, when a positive integer parameter m in Golomb coding meets a p-th power condition of 2, the number of binary leading zeros of N [ Q ] and A [ Q ] is calculated, a difference value k _ temp is obtained by subtraction, the difference value or the difference value plus 1 is taken as a Golomb coding variable according to a comparison result by calculating (N [ Q ] < < k _ temp < A [ Q ]).
Description
Technical Field
The present invention relates to an optimization method, an optimization device and a computer storage device, and more particularly, to an optimization method and an optimization device for continuous tone static image compression.
Background
JPEG-LS is a lossless/near-lossless compression standard for continuous tone still images, ISO-14495-1/ITU-T.87. Its core algorithm is LOCO-I (Low Complexity loss Compression for images). The LOCO-I algorithm can obtain compression efficiency similar to or even better than that of a plurality of current compression algorithms based on arithmetic coding, can keep lower complexity at the same time, and is widely applied to the fields of digital cameras, network transmission, wireless communication, medical imaging and the like.
The JPEG-LS coding block diagram is shown in FIG. 1, and includes several steps of context modeling, prediction, normal mode coding, run-length mode coding, etc.
After the context is determined, in the normal mode, calculations of predicted values, deviations, and corrections of prediction errors are performed. In this mode of operation, the final step of the encoding process is to encode the corrected prediction error. For this purpose, the encoder uses a scheme derived from golomb coding. This means that for each context only two statistical parameters, i.e. parameters representing the decay rate and the deviation of the distribution, respectively, need to be estimated. All possible prediction error values are mapped to non-negative values before encoding.
golomb coding was first introduced as a means of coding sequences of symbols that contain non-negative run lengths. For a positive integer parameter m, a golomb codeword of order m encodes an integer n greater than or equal to 0 into two parts: a unit 1 representation of the integer part (i.e., quotient) of n/m, and a binary representation of n mod m (i.e., remainder). The golomb codeword is optimal for non-negative integers of the geometric distribution. For each distribution in this form there is a parameter value m which allows the encoding to achieve the shortest possible average code length for all codewords that can be uniquely decoded as non-negative integers.
A special case of golomb code words is when m is a power p of 2, which results in a very simple encoding/decoding process: the code word of n is a number consisting of n high bits represented by unit 1 followed by n low bits. This special case is used in JPEG-LS and is labeled with the function g (k). k represents this golomb variable and m is equal to 2 to the power p.
The prediction error is encoded in the normal mode. To do this, the Golomb coding variable k needs to be computed using the variables A [0 … 364] and N [0 … 364] 364. The variable k is calculated in context and its calculation process is represented by the following code segment. The variable Errval is then mapped to a non-negative integer MErrval and encoded with the encoding function LG (k, LIMIT).
for(k＝0；(N[Q]<<k)<A[Q]；k++)；
Wherein, A [ Q ] is an absolute value variable for storing accumulated prediction error, N [ Q ] is a variable for storing the occurrence frequency of each context, A [ Q ] and N [ Q ] are unsigned non-negative 32-bit integer variables, Q is a quantization index variable, and k is a Golomb coding variable. A flow chart for this calculation is shown in fig. 2.
In the algorithm for calculating k, N [ Q ] < < k is calculated, k values are accumulated and are successively compared with A [ Q ], and finally the k value is obtained. The number of cycles is different because the values of N [ Q ] and A [ Q ] calculated by each substitution are different. The number of clocks that need to be consumed to calculate the k value is uncertain for each pixel of the image. Moreover, as can be seen from the flow chart, the calculation method has a feedback loop, so that the pipelined calculation of the k value cannot be realized.
Disclosure of Invention
The invention carries out pipeline optimization aiming at k value calculation of golomb-rice coding in lossless/near lossless image compression coding in JPEG-LS standard, in the k value calculation, a feedback loop existing in the calculation is removed, the calculated k value is completely consistent with the traditional algorithm result, and the pipeline calculation performance of the k value calculation is effectively improved.
The technical problem of the invention is mainly solved by the following technical scheme:
an optimization method for continuous tone static image compression is characterized in that when a positive integer parameter m in Golomb coding satisfies a power of p condition of 2, N [ Q ] is shifted to the left by k _ temp times and then compared with A [ Q ], according to the comparison result, a difference value or the difference value plus 1 is taken as a Golomb coding variable, wherein p is a positive integer, A [ Q ] is an absolute value variable for storing accumulated prediction errors, N [ Q ] is a variable for storing the occurrence frequency of each context, A [ Q ] and N [ Q ] are unsigned non-negative 32-bit integer variables, and Q is a quantization index variable;
defining a difference value as k _ temp, and specifically obtaining the difference value between the N [ Q ] binary leading zero number and the A [ Q ] binary leading zero number;
comparing the left-shifted result with A [ Q ], namely judging N [ Q ] < < k _ temp < A [ Q ], and selecting to execute according to the comparison result:
if N [ Q ] <k _ temp < A [ Q ] holds then the Golomb coding variable is k _ temp +1,
if N [ Q ] <k _ temp < A [ Q ] does not hold, the Golomb coding variable is k _ temp.
In the optimization method for continuous tone static image compression, the calculation process of the number of N [ Q ] binary Leading zeros is obtained by a zero count instruction clz (count Leading zeros).
In the above optimization method for continuous tone static image compression, the calculation process of the number of binary Leading zeros of a [ Q ] is obtained through a zero count instruction clz (count Leading zeros).
An apparatus for optimizing compression of a continuous tone static image, the apparatus being configured to compute a Golomb coding variable for which a positive integer parameter m satisfies a power of p condition of 2 in Golomb coding, p being a positive integer, comprising:
a shifting module: the device is used for shifting N [ Q ] left k _ temp times, wherein k _ temp is a positive integer, the difference value is defined as k _ temp, and the difference value is obtained by taking the difference value of the N [ Q ] binary leading zero number and the A [ Q ] binary leading zero number;
a result comparison module: shifting N [ Q ] by k _ temp times to the left, comparing the result after the left shift with A [ Q ], taking the difference or adding 1 to the difference as a Golomb coding variable according to the comparison result, comparing the result after the left shift with A [ Q ], namely judging N [ Q ] < < k _ temp < A [ Q ], and selecting to execute according to the comparison result:
if N [ Q ] <k _ temp < A [ Q ] holds then the Golomb coding variable is k _ temp +1,
if N [ Q ] <k _ temp < A [ Q ] does not stand, the Golomb coding variable is k _ temp;
wherein [ Q ] is an absolute value variable for storing the accumulated prediction error, N [ Q ] is a variable for storing the number of occurrences of each context, A [ Q ] is an absolute value variable for storing the accumulated prediction error, A [ Q ], N [ Q ] are unsigned non-negative 32-bit integer variables, and Q is a quantization index variable.
In the foregoing apparatus for optimizing compression of a continuous tone still image, the shift module includes:
leading zero number acquisition unit: used for obtaining N [ Q ] binary leading zero number and A [ Q ] binary leading zero number;
a number difference value comparison unit: is used for making difference value between N [ Q ] binary leading zero number and A [ Q ] binary leading zero number, and defining the difference value as k _ temp;
a shift unit: shift N [ Q ] k _ temp times to the left.
In the foregoing apparatus for optimizing compression of a continuous tone still image, the result comparing module includes:
a number difference value comparison unit: comparing the result of left-shifting N [ Q ] by k _ temp times with A [ Q ], namely judging N [ Q ] < < k _ temp < A [ Q ], and selecting to execute according to the comparison result:
if N [ Q ] <k _ temp < A [ Q ] holds then the Golomb coding variable is k _ temp +1,
if N [ Q ] <k _ temp < A [ Q ] does not hold, the Golomb coding variable is k _ temp.
In the aforesaid optimizing apparatus for continuous tone static image compression, the Leading zero number obtaining unit calculates the number of N [ Q ] binary Leading zeros by obtaining a zero count command clz (count Leading zeros); the Leading zero number obtaining unit calculates the number of A [ Q ] binary Leading zeros by obtaining the number of A [ Q ] binary Leading zeros through a zero count instruction CLZ (count Leading zeros).
An optimization apparatus for contone static image compression, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor is configured to perform the steps of the optimization method according to any one of claims 1 to 3 when executing the computer program.
Therefore, the invention has the following advantages: 1. the optimization method introduces a method for calculating the k value by a pipeline, and eliminates a feedback loop in the calculation of the traditional method. 2. The k value calculated by the optimized method is completely consistent with the result of the traditional method, and the pipeline calculation performance of k value calculation is effectively improved.
Drawings
FIG. 1 is a JPEG-LS encoding flow chart.
FIG. 2 is a flow chart of k value calculation of a conventional JPEGLS lossless compression algorithm.
FIG. 3 is a flow chart of k-value calculation of the JPEGLS lossless compression algorithm in the present invention.
Detailed Description
The technical scheme of the invention is further specifically described by the following embodiments and the accompanying drawings.
Example (b):
according to the formula of k value calculation, the invention introduces a method for calculating the k value by a production line, eliminates a feedback loop in the original method calculation, and ensures that each k value calculation consumes fixed clock number, thereby achieving the pipelining.
When a positive integer parameter m in Golomb coding meets a power-p condition of 2, the number of binary leading zeros of N [ Q ] and A [ Q ] is calculated, a difference value k _ temp is obtained by subtraction, then the N [ Q ] is shifted to the left by k _ temp times, the result after the left shift is compared with the A [ Q ], through calculation (N [ Q ] <k _ temp) < A [ Q ], the difference value or the difference value plus 1 is taken as a Golomb coding variable according to the comparison result, wherein A [ Q ] is an absolute value variable for storing accumulated prediction errors, N [ Q ] is a variable for storing the occurrence frequency of each context, p is a positive integer, A [ Q ] and N [ Q ] are unsigned non-negative 32-bit integer variables, Q is a quantization index variable, and k is a Golomb coding variable.
The flow chart for the improved k value calculation is shown in fig. 3 below:
1) calculating the number of binary Leading zeros of N [ Q ] and A [ Q ], wherein the number of the binary Leading zeros can be obtained through a zero counting instruction CLZ (count Leading zeros);
2) subtracting the number of leading zeros of A [ Q ] from the number of leading zeros of N [ Q ] to obtain k _ temp;
3) and performing decimal left shift operation on the N [ Q ], and performing left shift operation on the N [ Q ] by k _ temp times, namely calculating the N [ Q ] < < k _ temp.
4) Judging whether (N [ Q ] < < k _ temp < A [ Q ]) is true;
5) if N [ Q ] <k _ temp < A [ Q ] holds then the Golomb coding variable is k _ temp + 1,
if N [ Q ] <k _ temp < A [ Q ] does not hold, the Golomb coding variable is k _ temp.
Assuming that the number of clocks for calculating a non-negative integer variable is t0, the number of clocks required for calculating the k value by this method is t0+1, which is a fixed value, so that the k value calculation can be completely pipelined.
The invention also provides an optimization device for continuous tone static image compression, which aims at that a positive integer parameter m in golomb coding satisfies a power-p condition of 2, and comprises the following steps:
a shifting module: the shifting module is used for shifting N [ Q ] left k _ temp times, wherein k _ temp is a positive integer, and k _ temp is the difference value of N [ Q ] and A [ Q ], and the shifting module comprises:
leading zero number acquisition unit: used for obtaining N [ Q ] binary leading zero number and A [ Q ] binary leading zero number;
a number difference value comparison unit: is used for making difference value between N [ Q ] binary leading zero number and A [ Q ] binary leading zero number, and defining the difference value as k _ temp;
a shift unit: shift N [ Q ] k _ temp times to the left.
A result comparison module: shifting N [ Q ] to the left by k _ temp times, comparing the result after the left shift with A [ Q ], and taking the difference or adding 1 to the difference as a Golomb coding variable according to the comparison result;
wherein [ Q ] is an absolute value variable for storing the accumulated prediction error, N [ Q ] is a variable for storing the occurrence frequency of each context, A [ Q ] and N [ Q ] are unsigned non-negative 32-bit integer variables, and Q is a quantization index variable.
The result comparison module includes:
a number difference value comparison unit: comparing the result of left-shifting N [ Q ] by k _ temp times with A [ Q ], namely judging N [ Q ] < < k _ temp < A [ Q ], and selecting to execute according to the comparison result:
if N [ Q ] <k _ temp < A [ Q ] holds then the Golomb coding variable is k _ temp + 1,
if N [ Q ] <k _ temp < A [ Q ] does not hold, the Golomb coding variable is k _ temp.
Thirdly, the invention also provides a computer storage device, which stores a computer program capable of executing all the steps of the first deletion.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.
Claims (8)
1. An optimization method for continuous tone static image compression is characterized in that when a positive integer parameter m in Golomb coding satisfies a power of p condition of 2, N [ Q ] is shifted to the left by k _ temp times and then compared with A [ Q ], according to the comparison result, a difference value or the difference value plus 1 is taken as a Golomb coding variable, wherein p is a positive integer, A [ Q ] is an absolute value variable for storing accumulated prediction errors, N [ Q ] is a variable for storing the occurrence frequency of each context, A [ Q ] and N [ Q ] are unsigned non-negative 32-bit integer variables, and Q is a quantization index variable;
defining a difference value as k _ temp, and specifically obtaining the difference value between the N [ Q ] binary leading zero number and the A [ Q ] binary leading zero number;
comparing the left-shifted result with A [ Q ], namely judging N [ Q ] < < k _ temp < A [ Q ], and selecting to execute according to the comparison result:
if N [ Q ] <k _ temp < A [ Q ] holds then the Golomb coding variable is k _ temp +1,
if N [ Q ] <k _ temp < A [ Q ] does not hold, the Golomb coding variable is k _ temp.
2. The method of claim 1, wherein the number of N [ Q ] binary Leading zeros is computed by a zero count command CLZ (count Leading zeros).
3. The method of claim 1, wherein the calculation of the number of binary Leading zeros is performed by a zero count command clz (count Leading zeros).
4. An apparatus for optimizing compression of a continuous tone static image, the apparatus being configured to compute a Golomb coding variable for which a positive integer parameter m satisfies a power of p condition of 2 in Golomb coding, p being a positive integer, comprising:
a shifting module: the device is used for shifting N [ Q ] left k _ temp times, wherein k _ temp is a positive integer, the difference value is defined as k _ temp, and the difference value is obtained by taking the difference value of the N [ Q ] binary leading zero number and the A [ Q ] binary leading zero number;
a result comparison module: shifting N [ Q ] by k _ temp times to the left, comparing the result after the left shift with A [ Q ], taking the difference or adding 1 to the difference as a Golomb coding variable according to the comparison result, comparing the result after the left shift with A [ Q ], namely judging N [ Q ] < < k _ temp < A [ Q ], and selecting to execute according to the comparison result:
if N [ Q ] <k _ temp < A [ Q ] holds then the Golomb coding variable is k _ temp +1,
if N [ Q ] <k _ temp < A [ Q ] does not stand, the Golomb coding variable is k _ temp;
wherein [ Q ] is an absolute value variable for storing the accumulated prediction error, N [ Q ] is a variable for storing the number of occurrences of each context, A [ Q ] is an absolute value variable for storing the accumulated prediction error, A [ Q ], N [ Q ] are unsigned non-negative 32-bit integer variables, and Q is a quantization index variable.
5. The apparatus of claim 4, wherein the shifting module comprises:
leading zero number acquisition unit: used for obtaining N [ Q ] binary leading zero number and A [ Q ] binary leading zero number;
a number difference value comparison unit: is used for making difference value between N [ Q ] binary leading zero number and A [ Q ] binary leading zero number, and defining the difference value as k _ temp;
a shift unit: shift N [ Q ] k _ temp times to the left.
6. The apparatus of claim 5, wherein the result comparison module comprises:
a number difference value comparison unit: comparing the result of left-shifting N [ Q ] by k _ temp times with A [ Q ], namely judging N [ Q ] < < k _ temp < A [ Q ], and selecting to execute according to the comparison result:
if N [ Q ] <k _ temp < A [ Q ] holds then the Golomb coding variable is k _ temp +1,
if N [ Q ] <k _ temp < A [ Q ] does not hold, the Golomb coding variable is k _ temp.
7. The apparatus of claim 6, wherein the Leading zero number obtaining unit calculates the number of N [ Q ] binary Leading zeros by obtaining a zero count command clz (count Leading zeros); the Leading zero number obtaining unit calculates the number of A [ Q ] binary Leading zeros by obtaining the number of A [ Q ] binary Leading zeros through a zero count instruction CLZ (count Leading zeros).
8. An optimization apparatus for contone static image compression, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor is configured to perform the steps of the optimization method according to any one of claims 1 to 3 when executing the computer program.
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