JP4493551B2 - Data encoding apparatus, data decoding apparatus, data encoding method, data decoding method, and program - Google Patents

Description

  The present invention relates to a data encoding device, a data decoding device, a data encoding method, a data decoding method, and a program for encoding or decoding data based on an encoding table.

  In an imaging apparatus such as a digital camera, for example, in a single-lens reflex type model, imaging data called RAW data is recorded on a recording medium. This RAW data is simply converted into digital data after performing simple analog processing on the image signal obtained from the image sensor. By the way, in recent years, as the number of pixels of an image sensor of a digital camera is increasing, the data size of such RAW data is increasing. Accordingly, there are digital cameras that perform compression processing on RAW data to reduce the data size. However, it is assumed that the RAW data is retouched by the user, and it is desirable to perform lossless compression when performing compression processing.

The compression method is generally desired to have a high compression rate, but in the case of a compression method applied to an imaging device such as a digital camera, unlike the compression method applied to a single personal computer or the like, There are some more desirable conditions due to the restrictions on the specifications and the like, for example, as follows.
(1) Processing time is short (2) Buffer amount required for processing is small

  The condition (1) among these is a condition related to, for example, continuous shooting performance and battery consumption. Condition (2) is a condition related to the cost, size, weight, etc. of the digital camera.

  However, if both the condition (1) and the condition (2) are satisfied, the compression performance is likely to deteriorate.

  By the way, although there are various encoding methods, Huffman encoding used for image compression in JPEG or the like is one of well-known variable length encoding methods. When performing this Huffman coding, since it is possible to perform more efficient compression by using an appropriate coding table, there are various methods for selecting a coding table. Proposals have been made.

For example, Japanese Patent Laid-Open No. 9-65334 describes a technique for selecting an encoding table based on the ratio of zero coefficient signals. Therefore, it is considered that the technique described in the publication can achieve a high compression rate when the ratio of the zero coefficient signal is large, for example, in the case of a lossy compression method with quantization.
JP-A-9-65334

  However, in lossless compression, the ratio of the zero coefficient signal is often relatively small. Therefore, in the technique based only on the zero coefficient as described in JP-A-9-65334, the encoding table to be selected is not selected. It is difficult to determine with high accuracy. Further, in the technique for evaluating based on the ratio of the zero coefficient signal as described in the publication, since the coding efficiency (compression efficiency) with respect to a value other than the zero coefficient in the image block is not taken into consideration, the edge particularly When processing is performed on an image block including “”, the encoding efficiency may be extremely reduced.

  Therefore, not only lossy compression but also lossless compression, a compression method that can exhibit high compression performance while satisfying the above conditions (1) and (2) is desired.

  The present invention has been made in view of the above circumstances, and an object of the present invention is to provide a data encoding device, a data encoding method, and a program that have a short processing time, require a small amount of memory, and can exhibit high compression performance. It is said.

  It is another object of the present invention to provide a data decoding apparatus, a data decoding method, and a program that can decode the compressed data with a short processing time and a small required memory amount.

In order to achieve the above object, a data encoding apparatus according to a first invention comprises encoding table storage means for storing a plurality of preset encoding tables, and data values continuously within a predetermined range. detects the consecutive number of the data to be the run counter for successive number of said data repeating said detection for each reaches a predetermined number, the number of successive said data by the run counter reaches the predetermined number A lancet counter for detecting the number of lancets, which is the number of times the detection has been detected, and a plurality of encoding tables stored in the encoding table storage means according to the number of lancets detected by the lancet counter. A coding table selecting means for selecting any one of the coding tables, and a coding table selected by the coding table selecting means Based anda coding means for generating coded coded data the data, the above coding table, and a category representing the number significant bits of the data, the code word corresponding to this category, the corresponding The encoding means generates the encoded data by associating the code word with the significant bit part of the data, and the predetermined range can be set in a plurality of types. The run counter detects, for each of a plurality of set predetermined ranges, the number of consecutive data whose data values are continuously within the predetermined range, and The detection is repeatedly performed every time the continuous number reaches a predetermined number, and the lancet counter indicates that the continuous number of the data detected by the ran counter has reached the predetermined number. The number of detected lancets is detected corresponding to each of the plurality of types of predetermined ranges, and the encoding table selection means uses the lancet counter to detect the plurality of types of predetermined ranges. One of the plurality of encoding tables stored in the encoding table storage means is selected according to the number of lancets detected corresponding to each of the above .

  The data encoding apparatus according to the second invention is the data encoding apparatus according to the first invention, wherein the encoding target data to be noticed is predicted based on the encoding target data read in the past, and the prediction data is calculated. A prediction error calculating means for generating prediction error data by taking a difference between the target encoding target data and the prediction data calculated by the prediction means. This is prediction error data generated by the prediction error calculation means.

In the data encoding device according to a third invention, in the data encoding device according to the first invention, the predetermined range is a range in which an absolute value of the data is a predetermined threshold value or less, and the run counter is For each of a plurality of set thresholds, the continuous number of data in which the absolute value of the data is continuously less than or equal to the predetermined threshold is detected , and each time the continuous number of data reaches the predetermined number This detection is repeated .

A data encoding device according to a fourth invention is the data encoding device according to the third invention, wherein the encoding table storage means includes a plurality of encoding tables having different categories to which a codeword having the shortest code length is assigned. is intended to store, the coding table selection means, the number of the lancet that has been detected in correspondence with each of the plurality of types of threshold determined each to or greater than the predetermined number by the lancet counter, A codeword with the shortest code length is judged to have a high flatness when the lowest threshold value which is equal to or greater than a predetermined number is low, and a low flatness when the threshold is high, and when the flatness is high, the flatness is low. An encoding table is selected in which the category to which is assigned is a category representing a smaller number of significant bits.

A data encoding device according to a fifth invention is the data encoding device according to the first invention, wherein the data encoding device is generated by the encoding means and information indicating the type of the encoding table selected by the encoding table selection means. The encoded data is output as one file.

In the data encoding method according to the sixth aspect of the invention, the run counter detects the continuous number of the data whose data values are continuously within a predetermined range, and each time the continuous number of the data reaches the predetermined number. A first step of repeatedly performing the detection; a second step of detecting by the lancet counter the number of lancets that is the number of times that the continuation number of the data has been detected by the lance counter ; A third step of selecting any one of a plurality of preset encoding tables stored in accordance with the number of lancets detected by the lancet counter by the encoding table selecting means; by means, to generate encoded data by encoding the data based on the selected coding table by the coding table selection means A fourth step, the, above coding table is obtained by a category representing the number significant bits of the data, the code word corresponding to this category, the correspondence to the table, the fourth step Is to generate encoded data by associating the codeword with a significant bit part of the data, and the predetermined range can be set in plural types, and the first step is set For each of a plurality of types of predetermined ranges, the continuous number of the data in which the data value is continuously within the predetermined range is detected, and the detection is performed every time the continuous number of the data reaches the predetermined number. In the second step, the number of lancets, which is the number of times that the continuous number of the data detected by the run counter has been detected to reach the predetermined number, is determined by the plurality of types. The third step is performed in advance according to the number of lancets detected by the lancet counter corresponding to each of the predetermined ranges. This is a method for generating encoded data by selecting any one of a plurality of encoding tables that are set and stored .

A program according to a seventh invention causes a computer to detect the number of continuous data whose data values are continuously within a predetermined range and repeat the detection every time the number of continuous data reaches a predetermined number. A lancet counter for detecting the number of lancets, which is the number of times the continuation of the data has been detected to have reached the predetermined number, and the number of lancets detected by the lancet counter. In response, the encoding table selection means for selecting any one of the plurality of encoding tables that are set and stored in advance, and the encoding table selected based on the encoding table selected by the encoding table selection means a program for causing a data encoding means for generating encoded coded data as, the code The table is a table showing a correspondence relationship between a category representing the number of significant bits of the data and a code word corresponding to the category, and the encoding means includes the significant bit portion of the code word and the data. , And a plurality of types of the predetermined ranges can be set, and the run counter is configured to generate data for each of the set types of predetermined ranges. The continuation value is continuously within a predetermined range, and the detection is repeated every time the continuous number of data reaches the predetermined number. The number of lancets, which is the number of times that it has been detected that the number of consecutive data detected by the counter has reached the predetermined number, corresponds to each of the plurality of predetermined ranges. The encoding table selection means includes a plurality of codes set and stored in advance according to the number of lancets detected by the lancet counter corresponding to each of the plurality of types of predetermined ranges. A program characterized by selecting any one of the encoding tables .

According to an eighth aspect of the present invention, there is provided a data decoding device for detecting a coding table storage means for storing a plurality of preset coding tables and a continuous number of the data whose data values are continuously within a predetermined range. And a run counter for repeatedly performing the detection every time the continuous number of the data reaches a predetermined number, and the number of times that the continuous number of the data has been detected by the run counter. A lancet counter for detecting the number of lancets, and any one of the plurality of coding tables stored in the coding table storage means according to the number of lancets detected by the lancet counter and encoding table select means for selecting, coding the data based on the coding table selected by the coding table selection means Comprising encoding means for generating encoded data, and is the encoding table, a category that represents a significant number bits of the data, the code word corresponding to this category, the correspondence obtained by the table And the encoding means generates encoded data by associating the code word with a significant bit portion of the data, and the predetermined range can be set in plural types, and the run counter Detects, for each of a plurality of set predetermined ranges, the continuous number of the data in which the data value is continuously within the predetermined range, and the continuous number of the data reaches the predetermined number The lancet counter repeats the detection every time, and the lancet counter is a lancet that is the number of times that the continuous number of the data detected by the rancounter has reached the predetermined number. The encoding table selection means uses the lancet counter to correspond to each of the plurality of types of predetermined ranges. A data encoding device that selects one of the plurality of encoding tables stored in the encoding table storage unit according to the number of detected lancets. a data decoding apparatus for decoding encoded data, generated by, on the basis of information indicating the type of the selected code table, to reproduce the coding table used for coding Decoding for reproducing the data by decoding the encoded data based on the encoding table reproducing means and the encoding table reproduced by the encoding table reproducing means Means.

In the data decoding method according to the ninth aspect of the invention, the run counter detects the continuous number of the data whose data values are continuously within a predetermined range, and each time the continuous number of the data reaches the predetermined number. a first step of repeating said detection, the lancet counter, a second step of the number of successive said data by the run counter to detect the number of the lancet which is the number of times that has been detected to have reached the predetermined number, the code A third step of selecting any one of a plurality of encoding tables preset and stored in accordance with the number of lancets detected by the lancet counter by an encoding table selecting means; Accordingly, to generate encoded data by encoding the data based on the coding table selected by the coding table selection means The encoding table is a table showing a correspondence relationship between a category representing the number of significant bits of the data and a code word corresponding to the category. The fourth step includes The encoded data is generated by associating the code word with the significant bit portion of the data, and the predetermined range can be set in a plurality of types. For each of the predetermined ranges of types, the number of continuous data whose data values are continuously within the predetermined range is detected, and the detection is repeated each time the number of continuous data reaches the predetermined number. In the second step, the number of lancets, which is the number of times the continuous number of the data detected by the run counter has been detected to reach the predetermined number, is determined in the plurality of kinds of places. In the third step, the presetting is performed in accordance with the number of lancets detected by the lancet counter corresponding to each of the plurality of predetermined ranges. Data decoding for decoding encoded data generated by a data encoding method, wherein one of the plurality of stored encoding tables is selected . A method of reproducing the encoding table used for encoding based on the information indicating the type of the selected encoding table, and decoding the encoded data based on the reproduced encoding table; It is a method to reproduce data.

A program according to a tenth aspect of the invention causes a computer to detect the continuous number of the data whose data values are continuously within a predetermined range, and repeat the detection every time the continuous number of the data reaches a predetermined number. A lancet counter for performing, a lancet counter for detecting the number of lancets that is the number of times the continuation of the data has been detected by the lance counter, and the number of lancets detected by the lancet counter According to the encoding table selection means for selecting any one of the plurality of encoding tables set and stored in advance, based on the encoding table selected by the encoding table selection means a program for causing the data encoded by encoding means for generating encoded data as, the The encoding table is a table showing a correspondence relationship between a category representing the number of significant bits of the data and a code word corresponding to the category, and the encoding means is configured to determine whether the code word and the data are significant. The encoded data is generated by associating with the bit part, and the plurality of predetermined ranges can be set, and the run counter is set for each of the set predetermined ranges. , Detecting the continuous number of the data whose value continuously falls within a predetermined range, and repeatedly detecting the data every time the continuous number of the data reaches a predetermined number. The number of lancets, which is the number of times the number of consecutive data detected by the run counter is detected to reach the predetermined number, corresponds to each of the predetermined ranges of the plurality of types. The encoding table selection means is configured to detect a plurality of pre-set and stored in accordance with the number of lancets detected corresponding to each of the plurality of types of predetermined ranges by the lancet counter. A program for causing a computer to execute a process of decoding encoded data generated by a program characterized by selecting any one of the encoding tables . The encoding table used for encoding is reproduced based on the information indicating the type of the selected encoding table, and the encoded data is decoded and the data is reproduced based on the reproduced encoding table. A program for causing a computer to execute processing.

  According to the data encoding device, the data encoding method, and the program of the present invention, it is possible to exhibit high compression performance with a short processing time and a small required memory amount.

  In addition, according to the data decoding apparatus, data decoding method, and program of the present invention, the compressed data can be decoded with a short processing time and a small required memory amount.

  Embodiments of the present invention will be described below with reference to the drawings.

[Embodiment 1]
FIG. 1 to FIG. 21 show Embodiment 1 of the present invention. FIG. 1 is a block diagram showing the configuration of the data encoding device, and FIG. 2 is a block diagram showing the configuration of the data decoding device.

  As shown in FIG. 1, the data encoding device 1 includes a blocking unit 11, a prediction unit 12, a subtractor 13, an absolute value conversion unit 14, a flatness detection unit 15, and a Huffman table selection unit 16. And a Huffman encoder 17. Of these, image data is input to the block forming unit 11, and encoding table data is output from the Huffman table selection unit 16 as information indicating the type of the selected encoding table. The encoding unit 17 outputs encoded data. Further, the Huffman table selection unit 16 is a coding table storage unit that stores a plurality of types of preset Huffman coding tables as described later, and also functions as a coding table selection unit. One Huffman encoding table is selected from the plurality of types of Huffman encoding tables. Details of the data encoding device 1 will be described later along the operation with reference to FIGS. 4 and 6 to 8 and the like.

  Further, the data compressed by the data encoding device 1 is decoded by a data decoding device 2 as shown in FIG. That is, the data decoding apparatus 2 includes a decoding table creation unit 21 as a coding table reproduction unit, a Huffman decoding unit 22 as a decoding unit, an adder 23, a memory 24, and a prediction unit 25. It is configured. Among these, the encoding table data is input to the decoding table creation unit 21, the encoding data is input to the Huffman decoding unit 22, and the image data is output from the adder 23. . The details of the data decoding device 2 will be described later along the operation with reference to FIG.

  In FIG. 1 and FIG. 2, the adjustment of the mutual operation timing between the blocks is performed by a timing adjustment circuit (not shown).

  Furthermore, the flatness detection unit 15 of the data encoding device 1 is configured as shown in FIG. FIG. 3 is a block diagram illustrating a configuration of the flatness detection unit.

  The flatness detection unit 15 includes a comparison unit 31, a run counter 32, a comparison unit 33, a lancet counter 34, and a comparison unit 35. Among these, the prediction error data and the threshold th are input to the comparison unit 31, the external count reset signal is input to the run counter 32, the threshold th_run is input to the comparison unit 33, and the lancet counter 34 is input to the lancet counter 34. An external count reset signal is input, and the threshold value th_run_set is input to the comparison unit 35.

  The details of the flatness detection unit 15 will also be described later along the operation.

  Next, FIG. 4 is a flowchart showing compression processing by the data encoding device 1, FIG. 6 is a flowchart showing processing for pixel units of flatness detection processing, and FIG. 7 is processing for line units of flatness detection processing. FIG. 8 is a flowchart showing processing for each block unit of flatness detection processing, FIG. 9 is a diagram showing how image data is divided into blocks, and FIG. 10 is a diagram showing an example of pixel data of a block. 11 is a diagram showing the arrangement of the target pixel and neighboring pixels read before the target pixel, FIG. 12 is a diagram showing the prediction error data of the block obtained from the pixel data of FIG. 10, and FIG. 13 is the prediction error data of FIG. Fig. 14 is a diagram showing prediction error data converted into absolute values obtained by converting into absolute values, Fig. 14 is a chart showing threshold values and set values used in flatness detection, and Fig. 15 is an absolute value of Fig. 13. FIG. 16 is a chart showing the result of flatness detection obtained by applying the threshold values and setting values shown in FIG. 14 to the prediction error data, and FIG. 16 is a table of encoding tables set in advance according to the high, medium and low flatness. FIG. 17 is a diagram illustrating an example of prediction error data, FIG. 18 is a diagram illustrating an example of prediction error data, and FIG. 19 is a diagram illustrating a Huffman code obtained by encoding the prediction error data in FIG. .

  When this process is started, first, the blocking unit 11 divides input image data into blocks as shown in FIG. 9 (step S1). FIG. 9 shows an example in which image data of 32 × 56 pixels is divided into blocks of 8 × 8 pixels. As a result of the division, 7 × 4 blocks from B1 to B28 are obtained. Generated. Here, one image data is divided into 28 blocks, and one block is composed of 64 pixels. However, the present invention is not limited to this, so the number of blocks is more generally n, Assume that the number of pixels in a block is more generally m. Further, the present invention is not limited to dividing one image data into a plurality of pieces, and the entire image data may be processed as one block.

  Next, the prediction unit 12 performs processing on one block (a specific example, a block in which pixel data is arranged as shown in FIG. 10) among a plurality of blocks obtained by the division. The pixel data of the pixel of interest in the block is predicted based on the pixel data that has already been read in the block (step S2). Here, as shown in FIG. 11, if the target pixel in the block is denoted by x, the pixel in the block read before the target pixel x is, for example, the pixel a next to the left of the target pixel x. The pixel b adjacent to the upper side of the target pixel x and the pixel c adjacent to the upper left side of the target pixel x. In this case, the pixel reading order is to sequentially read from the leftmost pixel to the rightmost pixel for a certain line in the block, and when the reading of the line is completed, the next line in the block is read in the same manner. However, the reading order is not limited to this.

Then, assuming that the pixel values of the pixels a, b, and c are Ra, Rb, and Rc, respectively, and the predicted value (predicted data) of the target pixel x is Px, the predicted value Px is the spatial correlation of such pixel data. Based on the above, for example, the prediction unit 12 serving as a prediction unit calculates using a prediction formula as shown in the following Formula 1.
[Equation 1]
Px = max (Ra, Rb) (when Rc <min (Ra, Rb))
Px = min (Ra, Rb) (when Rc> max (Ra, Rb))
Px = Ra + Rb-Rc (at other times)
Here, the symbol max (x, y) means that the smaller value of x and y is taken, and the symbol min (x, y) takes the lesser value of x and y. This is also used in the following.

In addition, although the example using the prediction formula suitable for edge detection like Formula 1 was demonstrated here, the applicable prediction formula is not restricted to this, Other various prediction formulas can also be used. Is possible. For example, the following formulas 2 to 8 are given as some examples of prediction formulas. First, Equation 2 sets the pixel value Ra of the pixel a adjacent to the left of the target pixel as the predicted value Px of the target pixel x. This is considered that a highly accurate prediction value can be obtained when the correlation between pixels in the horizontal direction is high.
[Equation 2]
Px = Ra

Next, Equation 3 sets the pixel value Rb of the pixel b above and below the target pixel as the predicted value Px of the target pixel x. This is considered that a highly accurate prediction value can be obtained when the correlation between pixels in the vertical direction is high.
[Equation 3]
Px = Rb

Further, Equation 4 sets the pixel value Rc of the pixel c adjacent to the upper left of the target pixel as the predicted value Px of the target pixel x. This is considered that a highly accurate prediction value can be obtained when the correlation between pixels in the diagonal direction from the upper left to the lower right is high.
[Equation 4]
Px = Rc

Then, Formula 5 adds the pixel value Ra of the pixel a adjacent to the left of the pixel of interest x and the pixel value Rb of the pixel b adjacent to the upper side of the pixel of interest x, and from there, The pixel value Rc is subtracted to obtain the predicted value Px of the target pixel x. This is considered that an accurate predicted value can be obtained when there is regularity in the rate of change of the pixel value in the diagonal direction from the upper left to the lower right.
[Equation 5]
Px = Ra + Rb-Rc

In addition, Expression 6 calculates the pixel value Ra of the pixel a adjacent to the pixel of interest x to the pixel value Ra of the pixel b adjacent to the pixel of interest x from the pixel value Rb of the pixel b adjacent to the pixel of interest x. The value obtained by subtracting and dividing by 2 is added to obtain the predicted value Px of the target pixel x. This is considered that when the change rate of the pixel value of the pixel in the horizontal direction has regularity, a highly accurate predicted value can be obtained.
[Equation 6]
Px = Ra + {(Rb−Rc) / 2}

Further, Equation 7 subtracts the pixel value Rc of the pixel c adjacent to the upper left of the pixel of interest x from the pixel value Ra of the pixel a adjacent to the left of the pixel of interest x to the pixel value Rb of the upper pixel b of the target pixel x. Then, the value divided by 2 is added to obtain the predicted value Px of the target pixel x. This is considered that when the change rate of the pixel value of the pixel in the vertical direction has regularity, an accurate predicted value can be obtained.
[Equation 7]
Px = Rb + {(Ra−Rc) / 2}

Further, Expression 8 is an average value of the pixel value Ra of the pixel a adjacent to the left of the target pixel x and the pixel value Rb of the pixel b adjacent to the upper side of the target pixel x as the predicted value Px of the target pixel x. is there. This is considered that a highly accurate prediction value can be obtained when the correlation with the surrounding pixels is high (for example, when it is relatively flat).
[Equation 8]
Px = (Ra + Rb) / 2

  In addition, each prediction formula as described above is not limited to using only one for one image data, and may be used in combination. That is, for example, even if a prediction formula as shown in Formula 2 is basically used, when the pixel at the left end on the line is the target pixel, there is no pixel on the left side, so Formula 3 A combination such as using the prediction formula shown in FIG. The pixel data of any one or more pixels is not limited to the above-described prediction formulas, and may be any pixel that is read before the target pixel and has a spatial distance close to the target pixel. It is possible to calculate a predicted value using

  Further, in the example of calculating the prediction error data as shown in FIG. 12 from the pixel data shown in FIG. 10, when calculating the prediction value before calculating the prediction error data, the pixel at the upper left corner in the block is the pixel. The value 127 of the dynamic range 0 to 255 is a predicted value, and the predicted value is calculated using Equation 3 for the leftmost pixel from the second line to the eighth line in the block, and for the other pixels The predicted value is calculated using Equation 2.

Next, as shown in Equation 9, the subtractor 13 serving as a prediction error calculation unit calculates the prediction error value pred_diff by subtracting the prediction value Px predicted in step S1 from the actual pixel value Rx of the target pixel. (Step S3).
[Equation 9]
pred_diff = Rx-Px

  The prediction error value pred_diff calculated in this way is data to be subjected to Huffman coding, and is used for the processing in step S14 described later, and serves as an index for selecting a Huffman coding table. In order to determine the flatness, it is used as described below. Note that when the prediction value Px is calculated as described above for the pixel data of the block as shown in FIG. 10, the prediction error value pred_diff as shown in FIG. 12 is obtained.

  Subsequently, the absolute value converting unit 14 converts the prediction error value pred_diff into an absolute value, and calculates an absolute value of the prediction error value abs_pred_diff (step S4). The absolute value conversion for converting the prediction error value pred_diff shown in FIG. 12 into the prediction error value abs_pred_diff shown in FIG. 13 is performed by removing the negative sign when it is a negative value.

Note that the absolute value conversion means is not limited to this, and may be performed as shown in the following Expression 10, for example.
[Equation 10]
abs_pred_diff = pred_diff (when pred_diff ≥ 0)
abs_pred_diff = abs (pred_diff) −1 (when pred_diff <0)
Here, abs () on the right side of the second expression indicates that it takes an absolute value.

  Since there are various means other than these for absolute value conversion, it is of course possible to apply such other means.

  Next, the flatness detection unit 15 performs flatness detection 2 based on the comparison of the flatness detection 1 process based on the comparison with the first threshold (step S5) and the second threshold. This process is performed for each pixel unit (step S6).

  Note that the flatness detection 1 process in step S5 and the flatness detection 2 process in step S6 are the same process except that the value of the threshold th indicating a predetermined range is different. These processes will be described together with reference to FIG. Further, as shown in FIG. 14, the specific threshold th is 3 (threshold th1) in the flatness detection 1 process in step S5, and 31 (threshold th2 here) in the flatness detection 2 process in step S6. (Th2> th1 is satisfied). As a threshold th_run indicating a predetermined run length as described later, specifically, 4 is commonly used in step S5 and step S6.

  When the processing for the pixel unit of the flatness detection processing is started, first, the comparison unit 31 determines whether or not the predicted error value abs_pred_diff converted into an absolute value is equal to or smaller than a predetermined threshold th (step S31). .

  Here, if it is equal to or less than the threshold th, the run counter 32 counts up the run counter run_count provided therein (here, the count up is indicated by the symbol “run_count + 1”) (step S32). . The run counter run_count is a counter indicating how many pixels the prediction error value abs_pred_diff converted into an absolute value that is equal to or less than the threshold th is continuous.

  Then, the comparison unit 33 determines whether or not the run counter run_count is equal to or greater than a threshold th_run indicating a predetermined run length (step S34).

  Here, when the value is equal to or greater than the threshold th_run, the lancet counter 34 counts up the lancet counter run_set_count (again, the count-up is indicated by the symbol “run_set_count + 1” as described above) (step S35). ). The lancet counter run_set_count is a counter indicating how many sets (lancets) in which the prediction error value abs_pred_diff whose absolute value is equal to or less than the threshold th is the threshold th_run are detected in the block.

  Thereafter, the run counter 32 initializes the run counter run_count (that is, stores “0”) in response to the result of step S35 (step S36).

  On the other hand, if it is determined in step S31 that the absolute value of the prediction error value abs_pred_diff is larger than the predetermined threshold th, the run counter 32 initializes the run counter run_count (step S33).

  Thus, when step S33 or step S36 is completed, or when it is determined in step S34 that the run counter run_count is less than the threshold th_run, the process returns to the process shown in FIG.

  As described above, when the processing of step S5 and step S6 is completed, it is subsequently determined whether or not the processing for one line in the block has been completed (step S7). If the processing for one line is not completed, the process returns to step S2 to perform the above-described processing for the next pixel on the same line.

  If it is determined that the processing for one line has been completed, the flatness detection unit 15 performs processing for each line unit (step S8) of the flatness detection 1 processing corresponding to step S5 described above. The flat unit detection process corresponding to step S6 described above is performed for each line unit (step S9).

  In addition, since the process of step S8 and the process of step S9 perform the same process fundamentally, these processes are collectively demonstrated with reference to FIG.

  When this process is started, the run counter 32 receives an external count reset signal input from an external control means (not shown), etc., and resets an internal run counter run_count (step S41). Return to the indicated process.

  When the processing in step S8 and step S9 is completed in this way, it is subsequently determined whether the processing for m pixels is completed, that is, whether the processing for one block of interest is completed (step). S10). If the process for one block has not been completed, the process returns to step S2 to perform the process as described above for the next line in the same block.

  On the other hand, when it is determined that the processing for one block has been completed, the flatness detection unit 15 performs processing for each block unit of the flatness detection 1 processing corresponding to steps S5 and S8 described above (steps). S11) and the processing for the block unit (step S12) of the flatness detection 2 processing corresponding to steps S6 and S9 described above are performed.

  In addition, since the process of step S11 and the process of step S12 perform the same process fundamentally, these processes are demonstrated collectively with reference to FIG. In this process, a threshold th_run_set indicating a predetermined number of lancets is used. As a specific numerical value, 4 is used as shown in FIG.

  When this process is started, the comparison unit 35 determines whether or not the lancet counter run_set_count counted by the lancet counter 34 is equal to or greater than the above-described threshold th_run_set (step S51).

When the comparison unit 35 determines that the threshold value is equal to or greater than the threshold th_run_set, the comparison unit 35 outputs 1 by substituting 1 for the run flag run_flag indicating the flatness detection result (step S52), and determines that the threshold value is less than the threshold th_run_set. In this case, 0 is assigned to the run flag run_flag indicating the flatness detection result and output (step S53). Here, based on the threshold value and the set value as shown in FIG. 14, the determination result of the prediction error value abs_pred_diff that has been converted into an absolute value as shown in FIG. 13 is as shown in FIG. When the processing for one block is completed, the lancet counter run_set_count based on flatness detection 1 is 6 and the lancet counter run_set_count based on flatness detection 2 is 8. Since the threshold th_run_set is set to 4 as described above, both the run flag run_flag by flatness detection 1 and the run flag run_flag by flatness detection 2 are 1 as shown in FIG. .

  When the process of step S52 or step S53 is thus completed, the process returns to the process shown in FIG.

  As described above, when the processes of step S11 and step S12 are completed, the run flag run_flag output by the process of step S11 (this is referred to as run_flag1) and the run flag run_flag output by the process of step S12 (this) Huffman table selection unit 16 selects a Huffman encoding table (step S13). Here, as shown in FIG. 16, three Huffman coding tables are prepared according to the flatness of the block, one is a Huffman coding table according to high flatness, and the other is medium. A Huffman coding table corresponding to the flatness of the image and the last one is a Huffman coding table corresponding to the low flatness.

  The Huffman coding table corresponding to the high flatness assigns the shortest code length category code (codeword) when the prediction error becomes 0, and the short code length category code for the prediction error close to 0. Is a Huffman coding table.

  In addition, the Huffman coding table corresponding to the medium flatness assigns a category code having the shortest code length to a prediction error with an absolute value of 2 or 3, and the absolute value is close to 2 or 3. On the other hand, the Huffman coding table is such that a category code with a code length as short as possible is assigned.

  Further, the Huffman coding table corresponding to the low flatness assigns a category code having the shortest code length to a prediction error with an absolute value of 16 to 31, and for a prediction error with an absolute value close to 16 to 31. The Huffman coding table is such that a category code with a code length as short as possible is assigned.

  Then, when the run flag run_flag1 is 1 (in this case, the run flag run_flag2 is also 1), the Huffman table selection unit 16 determines that the flatness of the block is high, the run flag run_flag1 is 0, and the run flag run_flag2 is When it is 1, it is determined that the flatness of the block is medium, and when the run flag run_flag2 is 0 (in this case, the run flag run_flag1 is also 0), the block flatness is determined to be low. Yes. Based on the determination of the flatness, the Huffman table selection unit 16 selects one of the Huffman coding tables as shown in FIG.

  Subsequently, using the coding table selected by the Huffman table selection unit 16, the Huffman coding unit 17 as coding means performs Huffman coding of the prediction error value pred_diff calculated in Step S3 (Step S14). ).

  As is well known, the Huffman code includes a category code and significant bits (here, significant bits of prediction error data) (see FIG. 17). The category code is a code indicating the code length of the significant bit portion, and for example, 9-bit prediction error data “000001011” (decimal number “11”) as shown in FIG. 18 is obtained. Then, since the significant bits are the lower 4 bits, the category is “4” with reference to FIG. For this category 4, the category code “101” is assigned in the Huffman coding table when the flatness is high and the flatness is medium, and the category code “101” is assigned in the Huffman coding table when the flatness is low. 100 "is assigned. In the above-described example, since the Huffman coding table having a high flatness is selected, “101” is used as the category code. Therefore, the Huffman coded data is as shown in FIG. It becomes 7 bits of “1011011” and it can be seen that data compression is performed.

  Thus, when the Huffman encoding process is completed for each pixel data in one block, whether or not the process has been completed for n blocks, that is, the process of the entire image data to be processed is completed. Is determined (step S15). If the processing of the entire image data has not been completed, various parameters used for processing in units of blocks are reset as necessary, and the process returns to step S2 to return to the next in the same image data. The above-described processing is performed for this block. In addition, when the processing of the entire image data has been completed, this compression processing ends.

  The compressed image data is filed based on a predetermined file format in order to be recorded on a recording medium or the like via a file system or the like. FIG. 20 is a diagram illustrating an example of a file format for recording compressed image data.

  The compressed image file includes encoded data, and a header and a tag provided along with the encoded data.

  Then, of the three Huffman coding tables as described above, information indicating which Huffman coding table is applied to which block is recorded in the tag portion when, for example, a compressed image file is generated. It is like that.

  Here, FIG. 21 is a diagram showing a tag structure in the file format.

  The tag has a tag ID indicating the type of tag, a type indicating the type of the value recorded in the tag, a count indicating how many values of the type indicated by this type, and a value in the tag And an offset to a value indicating an address in which is stored.

  Then, in order to indicate the type of the Huffman coding table used for the block, for example, the following information is stored as tag information.

  First, in the tag ID, for example, information substantially indicating that “the value is stored is the information of the type of the Huffman coding table for each block” is stored.

  Next, a type indicating the amount of data (as a specific example, “char” indicating 1-byte data as used in the programming language C) is stored as the type. In the example described above, there are three types of Huffman coding tables (for example, “0” is assigned to high flatness, “1” is assigned to flatness, “2” is assigned to low flatness, etc.) Since a data amount of 2 bits is sufficient, it is more effective to reduce the file size by using a type with a data amount as small as possible. However, in practice, since data is often stored in units of 1 byte, in the example described above, for example, data for 4 blocks may be stored together in 1 byte.

  Furthermore, as the count, for example, the number of blocks is stored. However, in an example in which data for 4 blocks are stored together in 1 byte, the number of blocks is divided by 4, and a value obtained by adding 1 to the maximum integer not exceeding the number is stored.

  As the offset, for example, the relative data movement amount from the head of the tag ID to the address where the value is stored, or the data movement from the head of the tag area shown in FIG. 20 to the address where the value is stored. Quantity, etc. are stored.

  Thus, the Huffman coding table type information for each block stored as a set of values corresponding to each block is the above-described coding table data (data output from the Huffman table selection unit 16). , Data input to the decryption table creation unit 21).

  Note that a plurality of Huffman coding tables (that is, for example, a Huffman coding table as shown in FIG. 16) corresponding to the flatness stored in the data coding device 1 is the data decoding device 2 (for example, the decoding table). If the information is also stored in the creating unit 21), if only the information of the type of the Huffman coding table applied to each block is recorded in the tag as described above, the data decoding apparatus 2 will use the Huffman coding table. By selecting one Huffman encoding table from a plurality of stored Huffman encoding tables based on the type of information, it is possible to reproduce the Huffman encoding table used for encoding. On the other hand, when it is assumed that the data decoding apparatus 2 does not have a plurality of Huffman encoding tables identical to the data encoding apparatus 1 or may not exist (for example, a plurality of Huffman encoding tables). In addition to these, in addition to these, each Huffman code is further assumed to be decoded in a data decoding apparatus in which there is a plurality of Huffman coding tables. It is necessary to record the conversion table itself as tag information. At this time, the data decoding device 2 selects one Huffman encoding table from a plurality of Huffman encoding tables recorded as tag information based on the information of the type of the Huffman encoding table, and reads out the code. It is possible to reproduce the Huffman coding table used for the conversion.

  Next, FIG. 5 is a flowchart showing the decompression process performed by the data decoding apparatus 2.

  When this process starts, first, the decoding table creation unit 21 reads the encoding table data from the image file, reproduces the Huffman encoding table corresponding to each block, and outputs it to the Huffman decoding unit 22 (step S21). ).

  Subsequently, the Huffman decoding unit 22 reads the encoded data from the image file and decodes the prediction error value pred_diff for each pixel in the block based on the Huffman encoding table (step S22). .

  Then, the prediction unit 25 calculates the predicted value Px based on the already calculated pixel value stored in the memory 24 as described in step S2 of FIG. 4 (step S23).

Next, based on the prediction error value pred_diff decoded in step S22 and the prediction value Px calculated in step S23, a pixel value Rx is calculated as shown in the following equation 11 (step S24). .
[Equation 11]
Rx = Px + pred_diff

  Thereafter, it is determined whether or not the processing for one line in the block has been completed (step S25). If it has not been completed, the process returns to step S22 to perform the processing as described above for the next pixel in the same line. Repeat this step.

  If it is determined in step S25 that the processing for one line in the block has been completed, then whether or not the processing for m pixels has been completed, that is, the processing for one block has been completed. (Step S26), if not completed, the process returns to step S22, and the above-described processing is repeated for the next line in the same block.

  On the other hand, if it is determined in step S26 that the processing for one block has been completed, whether or not the processing has been completed for all n blocks, that is, the processing of the entire image data has been completed. (Step S27), and if not completed, the process returns to step S21 to read the encoding table data related to the next block and perform the above-described processing.

  In this way, when it is determined in step S27 that the processing of the entire image data has been completed, this expansion processing is ended.

  In the above description, image data is taken as an example of data to be processed. However, data that can be processed by the data encoding device 1 or the data decoding device 2 is not limited to this. .

  In the above description, processing is performed by the data encoding device 1 and the data decoding device 2, but processing may be performed by applying a data encoding method or a data decoding method to an existing arithmetic unit or the like. I do not care. Or you may make it make it process with a computer by the program for performing the process equivalent to the data encoding apparatus 1 or the data decoding apparatus 2. FIG.

  Furthermore, in the above description, the prediction error data is converted into an absolute value and then compared with a predetermined threshold value to detect the flatness, but the present invention is not limited to this. For example, the flatness may be detected according to whether prediction error data that has not been converted to an absolute value falls within a predetermined range.

  In the above description, the data to be subjected to Huffman coding and the flatness detection target is the prediction error data. However, the present invention is not limited to this, and other various data can be targeted. It is.

  In addition, in the above description, the Huffman coding table is exemplified as the coding table to be selected. However, the present invention is not limited to this, and a plurality of coding tables in other coding schemes are prepared in advance, and the flatness It is also possible to select a table to be used for encoding according to the above.

  According to the first embodiment, the flatness is detected in units of blocks, and the flatness corresponding to the detected flatness is selected from a plurality of Huffman coding tables set in advance corresponding to the plurality of flatnesses. Since the Huffman coding table is selected and Huffman coding is performed, high compression performance can be exhibited.

  And, because the number of lancets in which a predetermined number of prediction errors converted into absolute values equal to or less than a predetermined threshold value are detected, it is determined that the lancet is flat when the lancet is equal to or greater than the predetermined number. In addition, flatness can be detected at high speed in a short time without requiring complicated processing.

  Furthermore, since a plurality of predetermined threshold values to be compared with the prediction error converted to the absolute value are prepared, the flatness can be detected finely.

  In addition, since it is only necessary to perform the count by the run counter or the lancet counter when detecting the flatness, an increase in the amount of memory necessary for selecting the Huffman coding table can be substantially suppressed, which can be saved. It can be configured with a memory.

  In addition, the compressed data can be decoded with a short processing time and a small necessary memory amount.

  It should be noted that the present invention is not limited to the above-described embodiments, and various modifications and applications can be made without departing from the spirit of the invention.

  The present invention can be suitably used for a data encoding device, a data decoding device, a data encoding method, a data decoding method, and a program for encoding or decoding data based on an encoding table.

1 is a block diagram showing a configuration of a data encoding device according to Embodiment 1 of the present invention. The block diagram which shows the structure of the data decoding apparatus in the said Embodiment 1. FIG. The block diagram which shows the structure of the flatness detection part in the said Embodiment 1. FIG. 6 is a flowchart showing compression processing by the data encoding apparatus according to the first embodiment. 7 is a flowchart showing decompression processing by the data decoding apparatus according to the first embodiment. 5 is a flowchart showing processing for pixel units in flatness detection processing in the first embodiment. 5 is a flowchart showing processing for line units in flatness detection processing in the first embodiment. 5 is a flowchart showing processing for a block unit of flatness detection processing in the first embodiment. The figure which shows a mode that image data is divided | segmented into a block in the said Embodiment 1. FIG. FIG. 3 is a diagram illustrating an example of pixel data of a block in the first embodiment. The figure which shows arrangement | positioning with the attention pixel in the said Embodiment 1, and the neighboring pixel read before an attention pixel. The figure which shows the prediction error data of the block obtained from the pixel data of the said FIG. The figure which shows the prediction error data converted into the absolute value obtained by converting the prediction error data of the said FIG. 12 into an absolute value. The chart which shows each threshold value and setting value used in the flatness detection of the said Embodiment 1. FIG. FIG. 15 is a table showing flatness detection results obtained by applying the threshold values and setting values shown in FIG. 14 to the absolute value prediction error data shown in FIG. The table | surface which shows the example of the encoding table preset according to the said Embodiment 1 according to high / low / high of flatness. The figure which shows the structure of the Huffman code | symbol in the said Embodiment 1. FIG. The figure which shows an example of the prediction error data in the said Embodiment 1. FIG. The figure which shows the Huffman code | cord | chord obtained by encoding the prediction error data of the said FIG. FIG. 3 is a diagram showing an example of a file format for recording image data compressed in the first embodiment. The figure which shows the structure of the tag in the file format of the said Embodiment 1. FIG.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Data encoding apparatus 2 ... Data decoding apparatus 11 ... Blocking part 12 ... Prediction part (prediction means)
13: Subtracter (prediction error calculation means)
DESCRIPTION OF SYMBOLS 14 ... Absolute value conversion part 15 ... Flatness detection part 16 ... Huffman table selection part (a coding table storage means, a coding table selection means)
17 ... Huffman encoder (encoding means)
21 ... Decoding table creation unit (encoding table reproduction means)
22 ... Huffman decoding unit (decoding means)
DESCRIPTION OF SYMBOLS 23 ... Adder 24 ... Memory 25 ... Prediction part 31 ... Comparison part 32 ... Run counter 33 ... Comparison part 34 ... Lancet counter 35 ... Comparison part

Claims (10)

Encoding table storage means for storing a plurality of preset encoding tables;
A run counter for detecting the continuous number of the data whose value continuously falls within a predetermined range, and repeatedly performing the detection every time the continuous number of the data reaches a predetermined number ;
A lancet counter for detecting the number of lancets that is the number of times that the continuation number of the data has been detected to have reached the predetermined number by the lance counter;
Encoding table selecting means for selecting any one of the plurality of encoding tables stored in the encoding table storage means according to the number of lancets detected by the lancet counter;
Encoding means for generating the encoded data by encoding the data based on the encoding table selected by the encoding table selecting means;
Equipped with,
The encoding table is a table showing a correspondence relationship between a category representing the number of significant bits of the data and a code word corresponding to the category,
The encoding means generates encoded data by associating the code word with a significant bit part of the data,
A plurality of types of the predetermined range can be set,
The run counter detects, for each of a plurality of set predetermined ranges, the continuous number of the data whose data value is continuously within the predetermined range, and the continuous number of the data is predetermined. Each time the number is reached, the detection is repeated.
The lancet counter detects the number of lancets corresponding to each of the predetermined ranges of the plurality of types, which is the number of times that the continuous number of the data detected by the run counter is detected to reach the predetermined number. Is what
The encoding table selection means includes a plurality of encoding tables stored in the encoding table storage means according to the number of lancets detected by the lancet counter corresponding to each of the plurality of types of predetermined ranges. To select one of the encoding tables
A data encoding apparatus characterized by that. Prediction means for predicting the encoding target data of interest based on the encoding target data read in the past and calculating prediction data;
Prediction error calculation means for generating prediction error data by taking the difference between the target encoding target data and the prediction data calculated by the prediction means;
Further comprising
The data encoding apparatus according to claim 1, wherein the data is prediction error data generated by the prediction error calculation means. The predetermined range is a range in which the absolute value of the data is a predetermined threshold value or less,
The run counter detects, for each of a plurality of set thresholds, the number of consecutive data whose absolute value is continuously less than or equal to the predetermined threshold, and the number of consecutive data is predetermined. 2. The data encoding apparatus according to claim 1, wherein the detection is repeated every time the number is reached . The encoding table storage means stores a plurality of encoding tables having different categories to which codewords with the shortest code length are assigned,
The encoding table selection means determines whether or not the number of the lancets detected corresponding to each of the plurality of types of thresholds by the lancet counter is greater than or equal to a predetermined number, and has reached the predetermined number or more. When the lowest threshold is low, the flatness is high, and when it is high, the flatness is low. When the flatness is high, the category to which the codeword with the shortest code length is assigned is higher than when the flatness is low. 4. The data encoding apparatus according to claim 3, wherein an encoding table that is a category representing a small number of significant bits is selected . The information indicating the type of the encoding table selected by the encoding table selection unit and the encoded data generated by the encoding unit are output as one file. Item 4. The data encoding device according to Item 1 .   A first step of detecting, by a run counter, a continuous number of the data whose data value is continuously within a predetermined range, and repeatedly performing the detection every time the continuous number of the data reaches a predetermined number;
  A second step of detecting, by the lancet counter, the number of lancets, which is the number of times that the continuation number of the data is detected by the lance counter to reach the predetermined number;
  A third step of selecting any one of a plurality of preset encoding tables stored by the encoding table selection means according to the number of lancets detected by the lancet counter;
  A fourth step of generating the encoded data by encoding the data based on the encoding table selected by the encoding table selecting means by the encoding means;
  Have
  The encoding table is a table showing a correspondence relationship between a category representing the number of significant bits of the data and a code word corresponding to the category,
  The fourth step is to generate encoded data by associating the code word with a significant bit part of the data,
  A plurality of types of the predetermined range can be set,
  In the first step, for each of a plurality of set predetermined ranges, the continuous number of the data in which the data value is continuously within the predetermined range is detected, and the continuous number of the data is The detection is repeated every time a predetermined number is reached,
  In the second step, the number of lancets, which is the number of times that the continuous number of the data detected by the run counter is detected to reach the predetermined number, is determined corresponding to each of the predetermined ranges of the plurality of types. Is to detect,
  The third step is any one of the plurality of preset encoding tables stored according to the number of lancets detected by the lancet counter corresponding to each of the plurality of predetermined ranges. Select one encoding table
  A data encoding method characterized by the above.   Computer
  A run counter for detecting the continuous number of the data whose value continuously falls within a predetermined range and repeatedly performing the detection every time the continuous number of the data reaches a predetermined number;
  A lancet counter for detecting the number of lancets, which is the number of times that the continuation number of the data is detected to have reached the predetermined number by the lance counter;
  A coding table selecting means for selecting any one of a plurality of coding tables set and stored in advance according to the number of lancets detected by the lancet counter;
  Encoding means for encoding the data and generating encoded data based on the encoding table selected by the encoding table selecting means;
  Is a program for functioning as
  The encoding table is a table showing a correspondence relationship between a category representing the number of significant bits of the data and a code word corresponding to the category,
  The encoding means generates encoded data by associating the code word with a significant bit part of the data,
  A plurality of types of the predetermined range can be set,
  The run counter detects, for each of a plurality of set predetermined ranges, the continuous number of the data whose data value is continuously within the predetermined range, and the continuous number of the data is predetermined. Each time the number is reached, the detection is repeated.
  The lancet counter indicates the number of lancets, which is the number of times that the continuous number of the data detected by the run counter is detected to reach the predetermined number, corresponding to each of the predetermined ranges of the plurality of types, Is to detect,
  The encoding table selection means is configured to select one of a plurality of encoding tables stored in advance according to the number of lancets detected by the lancet counter corresponding to each of the plurality of predetermined ranges. Select one encoding table
  A program characterized by that.   Encoding table storage means for storing a plurality of preset encoding tables, and detecting the continuous number of the data whose data values are continuously within a predetermined range, and the continuous number of the data is a predetermined number And a lancet counter for detecting the number of lancets, which is the number of times that the continuation number of the data is detected to have reached the predetermined number by the run counter, Encoding table selection means for selecting any one of the plurality of encoding tables stored in the encoding table storage means according to the number of lancets detected by the lancet counter; and Encoding means for encoding the data based on the encoding table selected by the encoding table selection means and generating encoded data; The encoding table is a table showing a correspondence relationship between a category representing the number of significant bits of the data and a code word corresponding to the category, and the encoding means includes the code word And the significant bit part of the data are associated with each other to generate encoded data. The predetermined range can be set to a plurality of types, and the run counter can be set to a plurality of types of predetermined ranges. For each of the above, the number of continuous data whose data values are continuously within a predetermined range is detected, and each time the number of continuous data reaches a predetermined number, the detection is repeated. The lancet counter indicates the number of lancets, which is the number of times that the continuous number of the data detected by the run counter is detected to reach the predetermined number, and the predetermined range of the plurality of types. The encoding table selecting means detects the encoding according to the number of lancets detected by the lancet counter corresponding to each of the plurality of predetermined ranges. Decoding encoded data generated by a data encoding device, wherein one of the plurality of encoding tables stored in the table storage means is selected. The data decryption device of
  Based on the information indicating the type of the selected encoding table, encoding table reproducing means for reproducing the encoding table used for encoding;
  Decoding means for decoding the encoded data and reproducing the data based on the encoding table reproduced by the encoding table reproducing means;
  A data decoding apparatus comprising:   A first step of detecting a continuous number of the data whose value continuously falls within a predetermined range by a run counter, and repeatedly detecting the data every time the continuous number of data reaches the predetermined number; A second step of detecting the number of lancets, which is the number of times that the continuation number of the data has reached the predetermined number by the ran counter, and a detection by the lancet counter by the encoding table selection means A third step of selecting any one of a plurality of encoding tables set and stored in advance according to the number of lancets, and the encoding means selected by the encoding table selecting means. And a fourth step of generating the encoded data by encoding the data based on the encoded table. The table shows the correspondence between the category representing the number of significant bits of the data and the code word corresponding to the category, and the fourth step includes the significant bit portion of the code word and the data. Are generated in association with each other, and a plurality of types of the predetermined ranges can be set, and the first step is performed for each of the set types of predetermined ranges. The continuous value of the data in which the value of the data is continuously within a predetermined range is detected, and the detection is repeated every time the continuous number of the data reaches a predetermined number. The number of lancets, which is the number of times the number of consecutive data detected by the run counter has been detected to reach the predetermined number, is detected corresponding to each of the plurality of predetermined ranges. In the third step, among the plurality of encoding tables stored in advance according to the number of lancets detected by the lancet counter corresponding to each of the plurality of types of predetermined ranges. A data decoding method for decoding encoded data generated by a data encoding method, characterized by selecting any one of the encoding tables,
  Based on the information indicating the type of the selected encoding table, reproduce the encoding table used for encoding,
  Based on the reproduced encoding table, the encoded data is decoded and the data is reproduced.
  A data decoding method characterized by the above.   A run counter for detecting a continuous number of the data whose data values are continuously within a predetermined range, and repeatedly performing the detection every time the continuous number of data reaches the predetermined number; A lancet counter for detecting the number of lancets, which is the number of times that the counter has detected that the number of consecutive data has reached the predetermined number, and preset and stored according to the number of lancets detected by the lancet counter Coding table selecting means for selecting any one of the plurality of coded tables, and coding data obtained by coding the data based on the coding table selected by the coding table selecting means A program for functioning as an encoding means for generating the data, wherein the encoding table includes the presence of the data. The correspondence between the category representing the number of bits and the code word corresponding to this category is tabulated, and the coding means codes the code word and the significant bit part of the data in association with each other. A plurality of types of the predetermined range can be set, and the run counter has a predetermined data value for each of the set types of predetermined ranges. The continuous number of the data falling within the range is detected, and the detection is repeated every time the continuous number of the data reaches a predetermined number. The lancet counter detects the data detected by the run counter. The number of lancets, which is the number of times that it has been detected that the continuous number has reached the predetermined number, is detected corresponding to each of the predetermined ranges of the plurality of types, and the code The table selection means is any one of a plurality of encoding tables set and stored in advance according to the number of lancets detected corresponding to each of the plurality of types of predetermined ranges by the lancet counter. A program for causing a computer to execute a process of decoding encoded data generated by a program characterized by selecting an encoding table,
  Based on the information indicating the type of the selected encoding table, reproduce the encoding table used for encoding,
  A program for causing a computer to execute a process of decoding the encoded data and reproducing the data based on the reproduced encoding table.

Images