JP2001218062A - Device and method for image processing and storage medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To obtain the image data of desired compressibility by changing the compressibility of encoded image data. SOLUTION: An image file inputted part 502 inputs an image file including compressed image data, and when the compressibility of the inputted image data is decided, compressibility changing part 507 performs changing to the decided compressibility. In such a case, the code of an area of no interest of the image is eliminated and the compressibility of the image data is changed, or the code of an area of interest in the image data is eliminated and the compressibility of the image data is changed in the case the compressibility cannot be changed to a desired value only by the aforementioned procedure.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] 1. Field of the Invention [0002] The present invention relates to an image processing apparatus and method for changing a compression ratio of image data, and a storage medium.

[0002]

2. Description of the Related Art Radiation (X-ray, α-ray,
(β-rays, γ-rays, electron beams, ultraviolet rays, etc.), a part of this radiation energy is accumulated in the phosphor, and when this phosphor is irradiated with excitation light such as visible light, It is known that a phosphor emits photostimulated light in accordance with stored energy, and a phosphor exhibiting such properties is called an accumulating phosphor (stimulable phosphor). Using such a stimulable phosphor, radiation image information of a subject such as a human body is temporarily recorded on a stimulable phosphor sheet, and the stimulable phosphor sheet is scanned and irradiated with excitation light such as laser light. To emit light. The emitted light is photoelectrically read to obtain an image signal, and based on the image signal, a radiation image of a subject is output as a visible image on a recording material such as a photographic photosensitive material or a display device such as a CRT. An information recording / reproducing system has already been proposed by the present applicant (JP-A-55-12429, JP-A-56-1).
No. 1395).

In recent years, similarly to the case described above, a semiconductor sensor is used to generate X
Devices for capturing line images have been developed. These systems have the practical advantage of being able to record images over a very wide radiation exposure area as compared to conventional radiographic systems using silver halide photography. That is, an X-ray having a very wide dynamic range is read by a photoelectric conversion unit and converted into an electric signal, and the electric signal is used to display a radiation image on a recording material such as a photographic photosensitive material or a display device such as a CRT. By outputting the image as an image, it is possible to obtain a radiation image which is not affected by the fluctuation of the exposure amount of radiation.

[0004]

Since such an X-ray image contains a very large amount of information, the amount of the information is enormous when storing and transmitting the image information. There is a problem. For this reason, when storing and transmitting such image information, the redundancy of the image is removed or the deterioration of the image quality is hardly visually recognized.
High-efficiency coding is used to reduce the amount of image information by changing the content of the image.

For example, in JPEG recommended by the ISO and ITU-T as an international standard encoding method for still images, DPCM is used for lossless compression, and Discrete Cosine Transform (DCT) is used for lossy compression. ing. For details on JPEG, see Recommendation ITU-T.
Recommendation T. 81 | ISO / IEC 1091
8-1, etc., and are omitted here.

In recent years, discrete wavelet transform (DWT)
Many studies have been made on compression methods using transforms. The feature of the compression method using this DWT transform is that
The point is that the blocking artifacts seen in the CT transform do not occur.

[0007] In addition to X-ray images, radiation images typified by CT, MRI, etc., are determined by law to be stored for about five years.
It has been stored for more than 0 years. At this time, a low compression ratio is applied to relatively new radiation image data or image data that is frequently referred to, and a high compression ratio is applied to old image data or image data that is hardly referred to, thereby causing trouble. It is conceivable that the amount of image data to be stored is reduced as much as possible. Although this management criterion can be easily realized to some extent, the amount of calculation required to manually change the compression ratio of image data periodically becomes enormous, and there is no means for reducing the amount of calculation. In addition, with an increase in the amount of image data to be stored, it has become necessary to store image data at a higher compression rate.

SUMMARY OF THE INVENTION The present invention has been made in view of the above conventional example, and provides an image processing method and apparatus which can easily change the compression ratio of encoded image data to obtain image data having a desired compression ratio. The purpose is to provide.

Another object of the present invention is to compress image data by deleting a non-interest area or a code of a non-interest area and an interest area in a subband unit or a bit plane unit which is a feature of a code by DWT transform. An object of the present invention is to provide an image processing apparatus and method capable of changing a compression ratio to a desired compression ratio, and a storage medium.

It is another object of the present invention to provide an image processing apparatus and method and a storage medium capable of encoding a region of interest with a low compression ratio and high quality by deleting codes of a non-interest region of an image preferentially. It is in.

[0011]

In order to achieve the above object, an image processing apparatus according to the present invention has the following arrangement.
That is, input means for inputting an image file containing compressed image data, and compression rate changing means for changing a compression rate of the image data by deleting a code of a non-interest area in the image data input by the input means And the following.

In order to achieve the above object, an image processing apparatus according to the present invention has the following arrangement. That is, input means for inputting an image file including compressed image data,
First compression rate changing means for changing the compression rate of the image data by deleting a sign of a non-interest area in the image data input by the input means; And a second compression ratio changing unit for changing a compression ratio of the image data by deleting a code.

[0013] To achieve the above object, the image processing method of the present invention comprises the following steps. That is, an input step of inputting an image file including the compressed image data,
A compression ratio changing step of changing a compression ratio of the image data by deleting a code of a non-interest area in the image data input in the input step.

In order to achieve the above object, the image processing method of the present invention comprises the following steps. That is, an input step of inputting an image file including the compressed image data,
A first compression ratio changing step of changing a compression ratio of the image data by deleting a sign of a non-interest area in the image data input in the input step; And a second compression ratio changing step of changing a compression ratio of the image data by deleting a code.

[0015]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Preferred embodiments of the present invention will be described below in detail with reference to the accompanying drawings.

The feature of this embodiment is that, specifically, when changing the compression ratio of an image file compressed using DWT conversion, first, a non-interest area in the image file is changed. The code was deleted so that the target compression ratio was obtained. When further compression was necessary, the image was returned to a two-dimensional image, and the compression ratio was set again without recompressing. The feature of the present invention is to reduce the data amount of an image file by deleting a bit stream in units of subbands, which is a feature of encoding, and to further increase the compression ratio. Also,
In order to reduce the amount of stored image data, the bit stream may be truncated on a bit plane basis.

The details will be described below.

FIG. 1 is a block diagram showing a configuration of an image coding apparatus according to an embodiment of the present invention.

In FIG. 1, reference numeral 1 denotes an image input unit for inputting image data, which includes, for example, a scanner for reading a document image, an image pickup device such as a digital camera, or an interface unit having an interface function with a communication line. I have. Reference numeral 2 denotes a discrete wavelet transform unit that executes a two-dimensional discrete wavelet transform on an input image. Numeral 3 denotes a quantization unit for quantizing the coefficients subjected to the discrete wavelet transform by the discrete wavelet transform unit 2. Reference numeral 4 denotes an entropy encoding unit which entropy encodes the coefficients quantized by the quantization unit 3. 5
Is a code output unit that outputs the code encoded by the entropy encoding unit 4. Reference numeral 11 denotes an area specifying unit that specifies a region of interest of the image input from the image input unit 1.

The apparatus according to the first embodiment is similar to the apparatus shown in FIG.
The present invention can be applied to a case where a program for realizing this function is loaded into a general-purpose PC or workstation and operated, instead of a dedicated device as shown in FIG.

In the above configuration, first, the image input unit 1
, Pixel signals constituting an image to be encoded are input in raster scan order, and the output is input to the discrete wavelet transform unit 2. In the following description, an image signal input from the image input unit 1 will be described as a monochrome multi-valued image. However, if a plurality of color components such as a color image are encoded, each of RGB color components or luminance is encoded. The chromaticity component may be compressed as the single color component.

The discrete wavelet transform unit 2 performs a two-dimensional discrete wavelet transform process on an input image signal, and calculates and outputs a transform coefficient.

FIGS. 2A to 2C are diagrams illustrating the basic configuration and operation of the discrete wavelet transform unit 2 according to the present embodiment.

The image signal input from the image input unit 1 is stored in the memory 201, sequentially read out by the processing unit 202, subjected to a conversion process, and written in the memory 201 again.

FIG. 2B shows the configuration of the processing in the processing section 202 in the present embodiment. In the figure,
The input image signal is separated into a signal of an even address and a signal of an odd address by a combination of a delay element 204 and a down sampler 205, and is subjected to filter processing by two filters p and u. s and d respectively represent a low-pass coefficient and a high-pass coefficient when one-level decomposition is performed on a one-dimensional image signal, and are calculated by the following equations. I do.

D (n) = x (2n + 1) -floor ((x (2n) + x (2n + 2)) / 2) (Equation 1) s (n) = x (2n) + floor (( d (n-1) + d (n)) / 4 (Equation 2) where x (n) is an image signal to be converted, and in the above equation, floor {X} is the maximum value not exceeding X. Represents an integer value.

With the above processing, a one-dimensional discrete wavelet transform process is performed on the image signal from the image input unit 1. The two-dimensional discrete wavelet transform uses this 1
The two-dimensional discrete wavelet transform is sequentially performed in the horizontal and vertical directions of the image, and details thereof are known, and thus description thereof is omitted here.

FIG. 2C is a diagram showing an example of the structure of a two-level transform coefficient group obtained by the two-dimensional discrete wavelet transform process. The image signal is composed of coefficient sequences HH1, HL1, LH1 of different frequency bands. , LL. In the following description, these coefficient sequences are called subbands. Each sub-band obtained in this way is output to the subsequent quantization unit 3.

The region designating section 11 determines a region of interest (ROI: Region Of Interesting) to be decoded with higher image quality compared to the surrounding portion in the image to be encoded, and converts the target image into a discrete wavelet transform. Then, mask information indicating which coefficient belongs to the region of interest is generated.
The details of the area specifying unit 11 will be described later.

FIG. 3A is a diagram for explaining the principle of generating mask information.

As shown on the left side of FIG. 3A, when a star-shaped region is designated as the region of interest (hereinafter, designated region), the region designation section 11 converts the image including this designated region into a discrete wavelet. Calculate the portion occupied in each subband when the conversion is performed. The area indicated by the mask information is
This is a range including surrounding conversion coefficients necessary for restoring an image signal on the boundary of the designated area.

An example of the mask information calculated in this way is shown on the right side of FIG. In this example, FIG.
The mask information when the two-level discrete wavelet transform is performed on the image on the left of is calculated as shown in the figure. In this figure, a star-shaped portion is a designated area, and bits of mask information in this designated area are "1", and bits of other mask information are "0". Since the entire mask information has the same configuration as that of the transform coefficient by the two-dimensional discrete wavelet transform, it is determined whether or not the coefficient at the corresponding position belongs to the designated area by inspecting the bits in the mask information. be able to. The mask information generated in this way is output to the quantization unit 3.

Further, the area designating section 11 inputs parameters for designating image quality for the designated area from an input system (not shown). This parameter may be a numerical value representing the compression ratio assigned to the designated area or a numerical value representing the image quality.
In this case, the compression ratio to be assigned can be determined based on the region information of the captured image. For example, in the case of an X-ray image, the imaging part information is information indicating an imaging part and a direction, such as a chest front image and a head side image. These pieces of information may be input by an operator through an operation panel (not shown) of the image input unit 1 or may be transferred from the radiation information system prior to imaging. In general, since a chest image contains soft tissue, it is desirable not to increase compression rate much, and a bone image such as a head does not deteriorate significantly even if compression rate is increased. The area designating unit 11 calculates the bit shift amount B for the coefficient in the designated area from these parameters, and outputs it to the quantization unit 3 together with the mask.

Next, the configuration of the area specifying section 11 for automatically determining the specified area (region of interest) will be described in detail.

As shown in FIG. 1, the area designating section includes an image reducing section 301, an irradiation area extracting section 302, a histogram analyzing section 303, a binarizing processing section 304, and a morphological processing section 3.
05. In the image reducing unit 301, (2688
(336 × 33) for an input image of (× 2688) pixels
6) Output a reduced image of about pixels. In order to shorten the operation time of the subsequent processing, it is conceivable that the pixel value of the input image is 12 bits, the lower 4 bits of the 12 bits are deleted, and the image data is reduced and converted into 8-bit image data.

The irradiation area extraction unit 302 extracts how the X-ray incidence area is distributed over the entire input image. The X-ray incident area may be distributed over the entire surface of the input image, or may be irradiated with X-rays on a part (in this case, there is an aperture stop).

First, the determination of the presence or absence of the aperture stop for irradiation will be described with reference to FIGS.

FIG. 4A is a diagram showing an example of an input image. Here, if the input image area 400 has an irradiation aperture and there is an unirradiated part of X-rays, it is considered that the part is in the peripheral area of the image. For this reason, the average value of the pixel values in the peripheral area of the input image area 400 is compared with the average pixel value of the central part of the input image. Empirically, when the peripheral average pixel value is smaller than the central average pixel value by about 5% or more, it can be determined that the image has an aperture stop. In FIG. 4A, reference numeral 401 denotes an X-ray irradiation area, and 402 denotes a region of interest.

FIG. 4B is a diagram showing an example of the peripheral area 403 and the central area 404 in the input image area 400.

If there is an aperture stop, several profiles are extracted for each of the vertical and horizontal directions of the input image area 400. Two peak points are extracted from the secondary differential values of these extracted profiles. Then, the coordinates of the peak value of the second derivative with respect to the plurality of profiles are obtained, and the average line segment is obtained to obtain the line segment of the irradiation region.

FIG. 4C is a diagram showing an example of extracting the horizontal profile 405 and the vertical profile 406 as an example of the profile position.

FIG. 5A shows an example of secondary differential peak detection, where 407 indicates a profile, and dotted line 408 indicates secondary differential. FIG. 5B shows the detection positions of each profile, and these detection positions are indicated by circles.
FIG. 5C shows the irradiation area 409 finally extracted.
Is shown.

The histogram analyzer 303 calculates the frequency of pixel values for the region extracted as the irradiation region by the irradiation region extractor 302. Here, the correspondence between the pixel value and the input amount of X-ray is such that the larger the pixel value, the larger the incident amount. Based on the analysis of the histogram, it is determined whether or not there is any omission. Here, when there is a blank, there are two peaks, and it can be determined based on the two peaks.

In general, in imaging without any omission even though there is an aperture stop in the abdomen, chest, etc., only one peak appears despite the presence of bone and soft tissue. Techniques for detecting the number of these peaks are:
Assuming that the histogram is a waveform, a low-pass filter is applied to the histogram, and then secondary differentiation processing is performed. If the value of the secondary differentiation processing exceeds a threshold set empirically, it is determined that there is a peak. In rare cases, no peak may be detected, or three or more peaks may be detected. If no peak is detected, it is determined that there is no omission. If three or more are detected, two of the larger ones are selected, and a peak having a large pixel value is determined to be omission.

FIG. 6 is a diagram showing a histogram in the irradiation area and a peak 601 of the detected blank area.
Here, when it is determined that there is a skip, the binarization processing unit 304 performs a binarization process using the peak value SP of the skip. In addition, the peak value SP or more is omitted,
The area below this is determined to be a shooting target area.

Next, since there is a possibility that an isolated point exists or a blank region remains by the binarization processing unit 304, the morphology processing unit 305 performs a filtering process. Erosion is performed for about 3 to 5 pixels in order to remove the isolated point and the remaining transparent region. Thereafter, a labeling process is performed to limit the area to one continuous area. In this state, since there is a possibility that one continuous area has a hole, the hole is filled by performing a closing process.
The output result is a region of interest obtained by removing a blank region from the irradiation region 409. In the following description, it is assumed for convenience that the region of interest is the star shape shown in FIG.

The quantizing section 3 quantizes the inputted coefficient by a predetermined quantization step, and outputs an index for the quantized value. Here, the quantization is performed by the following equation.

Q = sign (c) floor (abs (c) / Δ) (Expression 3) sign (c) = 1; c ≧ 0 (Expression 4) sign (c) = − 1; c <0 (Expression 5) Here, c is a coefficient to be quantized. Ab
s (c) indicates the absolute value of c. In the present embodiment, the value of Δ includes “1”. In this case, no quantization is actually performed.

Next, the quantization section 3 changes the quantization index by the following equation based on the mask and the shift amount B input from the area specifying section 11.

Q ′ = q × 2 ^B ; m = 1 (Equation 6) q ′ = q; m = 0 (Equation 7) Here, m is the value of the mask at the position of the quantization index. By the above processing, only the quantization index belonging to the space area designated by the area designation unit 11 is shifted up by B bits.

FIGS. 3B and 3C are diagrams for explaining the change of the quantization index due to the shift up. In FIG. 3B, when three quantization indices exist in each of the three subbands, the value of the mask in the networked quantization index is “1”, and the shift number B is “2”. , And the post-shift quantization index is as shown in FIG.

The quantization index changed in this way is output to the entropy encoder 4 that follows.

The entropy coding unit 4 decomposes the quantization index input from the quantization unit 3 into bit planes, performs binary arithmetic coding for each bit plane, and outputs a code stream.

FIG. 7 is a diagram for explaining the operation of the entropy coding unit 4. In this example, there are three non-zero quantization indexes in a subband having a size of 4 × 4. "+13" and "-
6 ”and“ +3. ”The entropy coding unit 4 scans this area to scan the maximum value M (“ 1 ”in this example).
3 "), and the number of bits S required to represent the maximum quantization index is calculated by the following equation.

S = ceil (log ₂ (abs (M))) (Equation 8) Here, ceil (x) represents the smallest integer value among integers greater than or equal to x.

In FIG. 7, since the maximum coefficient value is "13", the number of bits S representing this is "4", and the 16 quantization indexes in the sequence are as shown on the right side of FIG. Processing is performed in units of four bit planes. First, the entropy coding unit 4 performs binary arithmetic coding on each bit of the most significant bit plane (represented by the MSB in the figure), and outputs it as a bit stream. Next, the bit plane is lowered by one level, and similarly, each bit in the bit plane is encoded and output to the code output unit 5 until the target bit plane reaches the least significant bit plane (represented by LSB in the figure). At this time, the code of each quantization index is entropy-coded immediately after the first non-zero bit is detected in the bit plane scanning.

There are two types of entropy coding: resolution scalable and SNR scalable, and the bit stream deletion strategies are different.

First, encoding for performing resolution scalability will be described.

FIG. 8 is a schematic diagram showing the structure of a code string generated and output in this manner.

FIG. 8A shows the entire structure of a code string, where MH is a main header and THi (i = 0 to n-
1) indicates a tile header, and BSi (i = 0 to n-1) indicates a bit stream. As shown in FIG. 2B, the main header MH includes the size of the image to be encoded (the number of pixels in the horizontal and vertical directions), the tile size when the image is divided into a plurality of rectangular tiles, and each color component. The number of components indicating the number, the size of each component, and component information indicating the bit precision are provided. In the present embodiment, since the image is not divided into tiles, the tile size and the image size take the same value, and when the target image is a monochrome multi-valued image, the number of components is “1”.

Next, the configuration of the tile header TH is shown in FIG.
Shown in The tile header TH includes a tile length including a bit stream length and a header length of the tile, an encoding parameter for the tile, mask information indicating a designated area, and a bit shift number for a coefficient belonging to the area. The coding parameters include the level of the discrete wavelet transform, the type of filter, and the like.

FIG. 8D shows the structure of a bit stream according to the present embodiment. In FIG. 8B, the bit stream is grouped for each sub-band, and the sub-bands (LL) having the smaller resolutions are set at the head. Are arranged in the order of increasing. Further, in each subband, codes are arranged in units of bit planes from the upper bit plane (bit plane S-1) to the lower bit plane (bit plane 0).

With such a code arrangement, it is possible to perform hierarchical decoding as shown in FIG. 13 described later.

Next, SNR scalable will be described.

FIG. 9 is a schematic diagram for explaining the structure of a code string generated and output at the time of SNR scalability.

FIG. 9A shows the entire structure of a code string, where MH is a main header and THi (i = 0 to 0).
n-1) is a tile header, and BSi (i = 0 to n-1) is a bit stream. The main header MH includes the size of the image to be encoded (the number of pixels in the horizontal and vertical directions), the tile size when the image is divided into tiles as a plurality of rectangular areas, and each color, as shown in FIG. Component information indicating the number of components indicating the number of components, the size of each component, and bit precision is provided. In the present embodiment, since the image is not divided into tiles, the tile size and the image size take the same value. When the target image is a monochrome multi-valued image, the number of components is “1”.
It is.

Next, the structure of the tile header TH is shown in FIG.
Shown in

The tile header TH includes a tile length including a bit stream length and a header length of the tile, an encoding parameter for the tile, mask information indicating a designated area, and a bit shift for a coefficient belonging to the area. Have a number. The encoding parameters include
It includes the level of the discrete wavelet transform, the type of filter, and the like.

FIG. 9D shows the configuration of a bit stream according to the present embodiment. The bit stream is grouped in units of bit planes, and is shifted from the upper bit plane (bit plane S-1) to the lower bit plane (bit plane). 0). In each bit plane, the result of encoding the bit plane of the quantization index in each subband is sequentially arranged in subband units. In the figure, S
Indicates the number of bits required to represent the maximum quantization index. The code string generated in this way is output to the code output unit 5.

By adopting such a code arrangement, hierarchical decoding as shown in FIG. 14, which will be described later, can be performed.

In the above-described embodiment, the compression ratio of the entire image to be encoded can be controlled by changing the quantization step Δ.

As another method, in the present embodiment, it is possible to restrict (discard) the lower bits of the bit plane to be encoded in the entropy encoding unit 4 in accordance with a necessary compression ratio. In this case, not all bit planes are coded, and the bit planes from the upper bit plane to the number of bit planes corresponding to the desired compression ratio are coded and included in the final coded sequence.

As described above, by adopting the function of limiting the lower-order bit plane, only bits corresponding to the designated area shown in FIG. 3 are included in the code string. That is, by compressing only the designated area at a low compression rate, it is possible to encode a high-quality image.

Next, a method of decoding a bit stream encoded by the above-described image encoding apparatus will be described.

FIG. 10 is a block diagram showing the configuration of an image decoding apparatus according to the present embodiment. 6 is a code input section, 7 is an entropy decoding section, 8 is an inverse quantization section, and 9 is an inverse discrete wavelet transform section. Reference numeral 10 denotes an image output unit.

The code input unit 6 receives, for example, a code string coded by the above-described coding apparatus, analyzes a header included in the code string, extracts parameters necessary for the subsequent processing, and if necessary, performs processing. Or sends the corresponding parameters to the subsequent processing unit. Further, the bit stream included in the input code sequence is output to the entropy decoding unit 7.

The entropy decoding unit 7 decodes and outputs the bit stream in bit plane units. FIG. 11 shows the decoding procedure at this time.

The left side of FIG. 11 shows a flow of sequentially decoding one area of the sub-band to be decoded on a bit plane basis and finally restoring the quantization index. The bit planes are decoded in order.
The reconstructed quantization index is used as the inverse quantization unit 8
Is output to

The inverse quantization unit 8 restores discrete wavelet transform coefficients from the input quantization index based on the following equation.

C ′ = Δ × q / 2 ^U ; q ≠ 0 (Equation 9) c ′ = 0; q = 0 (Equation 10) U = B; m = 1 (Equation 11) U = 0; m = 0 (Equation 12) Here, q is a quantization index, Δ is a quantization step, and Δ is the same value used at the time of encoding. B is the number of bit shifts read from the tile header, and m is the value of the mask at the position of the quantization index. c ′ is a restored transform coefficient, which is a restored coefficient represented by s or d at the time of encoding. The transform coefficient c ′ is output to the subsequent inverse discrete wavelet transform unit 9.

FIG. 12 shows an inverse discrete wavelet transform unit 9.
FIG. 1 is a block diagram showing the configuration and processing thereof.

In FIG. 9A, the input transform coefficients are stored in a memory 901. The processing unit 902 performs one-dimensional inverse discrete wavelet transform, sequentially reads out transform coefficients from the memory 901 and performs processing to perform two-dimensional inverse discrete wavelet transform. The two-dimensional inverse discrete wavelet transform is executed in the reverse procedure of the above-described forward discrete wavelet transform, but the details are known and will not be described.

FIG. 11B shows a processing block of the processing unit 902. The input conversion coefficient is subjected to two filter processings of u and p, and the upsampler 12
After being up-sampled by 01, they are superimposed to output an image signal x ′. These processes are performed by the following equations.

X ′ (2n) = s ′ (n) −floor ((d ′ (n−1) + d ′ ((n)) / 4) (Expression 13) x ′ (2n + 1) = d ′ (n) + floor ((x ′ (2n) + x ′ (2n + 2)) / 2) (Expression 14) Here, (Expression 1), (Expression 2), (Expression 13), and (Expression 1)
Since the discrete wavelet transform in the forward and backward directions according to 4) satisfies the perfect reconstruction condition, the quantization step Δ is “1” in the present embodiment, and all the bit planes are decoded in the bit plane decoding. If so, the restored image signal x 'matches the signal x of the original image.

The image is restored by the above processing and output to the image output unit 10. Here, the image output unit 10 may be an image display device such as a monitor or a storage device such as a magnetic disk.

Next, a description will be given of an image in the case of encoding by spatial scalability.

A display mode of an image when an image is restored and displayed by the above-described procedure will be described with reference to FIG.

FIG. 9A is a diagram showing an example of a code string, and the basic configuration is based on FIG. Here, the entire image is set as a tile, and therefore, only one
Tile header (TH0) and bit stream (B
S0). This bit stream (BS
0), as shown in the figure, codes are arranged in order of increasing resolution from LL, which is a subband corresponding to the lowest resolution, and in each subband, an upper bit plane (bit plane (S Codes are arranged from -1)) to the lower bit plane (bit plane 0).

The decoding device sequentially reads the bit stream, and displays an image when the code corresponding to each bit plane is decoded. FIG. 3B is a diagram showing each subband, the size of an image displayed corresponding to the subband, and a change in a reproduced image accompanying decoding of a code string of each subband. In the figure, the code sequence corresponding to LL is sequentially read, and the image quality is gradually improved as the decoding process of each bit plane progresses. At this time, the star-shaped part which has become the designated area at the time of encoding is restored with higher image quality than other parts.

This is because, at the time of encoding, the quantization unit 3 shifts up the quantization index belonging to the specified area, so that the quantization index becomes earlier than other parts during bit plane decoding. This is because it is decrypted. The reason why the designated area portion is decoded with high image quality is the same for other resolutions.

Further, when all the bit planes have been decoded, the designated area and the other parts are the same in image quality. However, if the decoding is discontinued at an intermediate stage, the designated area is more than the other areas. Also, an image restored with high image quality can be obtained.

Next, a description will be given of an expansion in the case of encoding with SNR scalable.

A display mode of an image when an image is restored and displayed by the above-described procedure will be described with reference to FIG.

FIG. 9A shows an example of a code string. The basic configuration is based on FIG. 9, but here, the entire image is set as a tile, and therefore, the code string is included in the code string. Contains only one tile header (TH0) and bit stream (BS0). This bit stream BS
As shown in the figure, a code is assigned to 0 from the most significant bit plane (bit (S-1)) to the least significant bit plane (bit 0).

The decoding apparatus sequentially reads the bit stream and displays an image when the code of each bit plane is decoded. In FIG. 3B, the image quality is gradually improved from bit S-1 to bit S-2,..., Bit 0 as the decoding process of each bit plane progresses. The lost star-shaped part is restored to higher image quality than the other parts.

This is because, as described above, the quantization unit 3 bit-ups the quantization index belonging to the designated area at the time of encoding by the encoding apparatus. Is decoded earlier for the other parts.

Further, when all bit planes have been decoded, the designated area and the other parts have the same image quality. However, if the decoding is terminated in the middle, the designated area is higher than the other areas. An image restored to the image quality is obtained.

In the above-described embodiment, the amount of coded data to be received or processed is reduced by limiting (ignoring) the lower bit planes to be decoded in the entropy decoding unit 7, and consequently the compression ratio is controlled. It is possible. By doing so, it is possible to obtain a decoded image of a desired image quality only from encoded data of a necessary data amount. If the quantization step Δ at the time of encoding is “1” and all the bit planes have been decoded at the time of decoding, it is necessary to realize lossless encoding / decoding in which the restored image matches the original image. Can also.

When the function of limiting the lower bit plane is used, the code string to be decoded contains only bits corresponding to the designated area shown in FIG. 4 more than the other areas. The same effect as decoding image data obtained by encoding only the specified area as a high-quality image with a low compression ratio can be obtained.

Hereinafter, features of the embodiment of the present invention will be described.

FIG. 15 is a block diagram showing the configuration of the image processing apparatus according to the embodiment of the present invention.

In the figure, reference numeral 501 denotes a DWT encoder (encoding unit) having a configuration as shown in FIG. 1, for example.
, And the newly input image is encoded using the DWT transform. However, some images have already been compressed by another encoding method such as DCT transform. In this case, the image data is once decoded into a two-dimensional image by the above-described decoding device and the like, and then the DWT is re-used. The data is input to the encoder 501 and encoded.

The image data thus encoded by the DWT encoder 501 is stored in a storage unit (not shown) inside the device via the internal bus 505, or is stored in an external storage device (not shown) via the network 506. Is done. The list of all the stored images is managed by the image file management unit 502.

Here, when the input image is, for example, a medical image, it is desired that the image be stored for a long time as evidence of medical treatment. Taking an X-ray image as an example, one X-ray image has an image data amount of 10 to 20 megabytes.
There may be cases where the number of sheets also increases. Therefore, in consideration of storing such an image for a long time, it is impossible to store the image without compression. However, compressing an X-ray image immediately after imaging or an X-ray image of a patient who is still undergoing medical treatment at a high compression rate requires observing a subtle difference between the X-ray images in follow-up observation. It is not appropriate considering that.
Therefore, it is necessary to determine an appropriate compression ratio for each of the X-ray images to be managed, and to compress and store the image according to the determined compression ratio.

The image file management unit 502 periodically
For example, the attribute of the image file being checked is checked every day or every week. The image file may be managed inside the device via the internal bus 505, or may be stored and managed in an external storage device (not shown) via the network 506. The image file management unit 502 may refer to the attribute file managed in each storage device when the attribute information of the image file is changed or managed. The attributes of the image file include, in addition to the patient information, the type of the image, the imaging region, the number of days elapsed since the imaging date, the number of days elapsed since the diagnosis date referring to the image, and the amount of time elapsed since the last access date to the image. There are a number of days (the number of elapsed days is a time factor), and a compression ratio at the present time.

As the types of such images, X-ray images, CT images, MRI images, and the like can be considered. CT, M
Since the RI image is generally an image having a higher density resolution than the X-ray image, it is possible to increase the compression ratio as compared with the X-ray image. Further, the imaging part information is effective as information relating to the X-ray image. For example, a chest image often contains finer information than a head image, and thus has a feature that it is difficult to increase the compression ratio. The number of days that have elapsed since the imaging date and the number of days that have elapsed since the image diagnosis date serve as data for determining the compression ratio of the image based on the legal preservation obligation of the image, guidelines for the storage period of the hospital, and the like.

The compression ratio of the image is temporarily determined on the basis of the above criterion. The final compression ratio is determined based on the number of days elapsed since the last access to the image and the state of hospitalization of the patient. The rate is determined. For example, in the case of an image that is very old, such as seven years ago, a compression ratio of about 50% is determined to be sufficient by a primary decision based on the shooting date and the like. If you are going to the hospital
It is finally determined so that the compression ratio of the image is suppressed to about 20%.

In this way, the compression ratio of the image is finally determined by the image file management unit 502, and the compression ratio is compared with the compression ratio of the current image file. File input unit 5
In the case where an image is taken in by 04 or the image is input from an external device, the image may be transferred from the external device. At the same time, the finally determined compression ratio is transferred to the compression determining unit 503 and presented to the compression ratio changing unit 507.

The compression ratio changing means 507 analyzes the input image file, and calculates the cut amount of the bit stream so as to achieve the target compression ratio. Here, regarding the image in which the region of interest is set, the method of deleting the code bit stream will be described.

Here, assuming that the above-mentioned star-shaped portion in FIG. 3A is a region of interest, the region of interest is set for each sub-band. Also, before the region of interest is encoded, FIG.
From (b), a bit shift as shown in FIG. 3 (c) is performed. That is, in FIG. 3C, a 3-bit bit shift is performed on the region of interest shown in gray.

In the code of the non-interest area shown in FIG. 3C, if the lower two bit planes are deleted,
For the rightmost block (corresponding to “+3” in FIG. 7), the sign of the non-interest area can be completely eliminated. However, regarding the blocks on the left side (corresponding to “+13” in FIG. 7) and the center (corresponding to “−6” in FIG. 7), the sign of the non-interest area cannot be completely deleted.

FIG. 16 is a flowchart for explaining how the compression ratio changing unit 507 in FIG. 15 makes the compression ratio of the image data of the image file reach the target compression ratio.

First, in step S11, as described with reference to FIG. 3C, it is determined whether or not the target compression ratio can be reached only by deleting the low bit plane, and if it can be reached, the process proceeds to step S12. Then, the low bit plane is deleted.

On the other hand, if the target compression ratio cannot be reached only by deleting the low bit plane, step S13
The entropy decoding is performed on the compressed image data, and the image data of the region of interest of the decoded image data is bit-shifted (step S14).

For example, a description will be given based on the example of FIG. 3C described above.
If the bit plane is shifted by three bits and the bit plane is shifted by three bits, the compression ratio is further increased as compared with the case of the above-described example (2-bit shift). However, if the bit shift amount of the region of interest becomes larger than the bit amount of the original image data in order to obtain the target compression ratio, it means that the non-interest region of the image data is not encoded at all. The bit-shifted image data is encoded by the encoding device shown in FIG. 1 (step S15).
Then, it is determined in step S16 whether or not the target compression rate can be obtained by deleting the low bit plane from the encoding result after the bit shift, and if the target compression rate is obtained, the processing is performed. finish.

However, there is a case where the target compression ratio is not reached even if the non-interest area is not encoded at all. In this case, the process proceeds from step S16 to step S17, and in step S18 or S19, the bit rate corresponding to the region of interest is deleted or the subband is deleted, so that the compression ratio can be further increased. At this time, the high frequency component of the sub-band to be deleted is deleted first. However, the data compression here can be realized by deleting the bit stream. Such removal of the bit stream differs depending on the coding method of the resolution scalability and the SNR scalability.

Resolution scalability is based on image transfer,
At the time of reading, first a small image is displayed quickly,
A large image is displayed together with sequential transfer or reading of a file. This example is shown in FIG. 13 described above.

In this case, as shown in FIG. 13A, the encoding is performed in units of sub-bands. Therefore, in order to increase the compression ratio, in step S18, for example, the highest sub-band HH1 What is necessary is just to delete information. Further, if the compression rate becomes too high when the sub-band HH1 is deleted, since the encoding is performed for each bit plane in the sub-band HH1, it is deleted from the lowest-level bit plane (bit plane 0). Just do it.

Next, the case of SNR scalability will be described.

In this SNR scalability, an image is encoded so that an image having a good SNR is displayed together with transfer or reading. An example will be described with reference to FIG. As shown in FIG. 14A, in this method, since encoding is performed in units of bit planes, in order to further increase the compression ratio, it is necessary to delete the lower bit plane (bit 0) in units of bit planes. Easy. In FIG. 14A, bit 0 is the lowest level bit plane. However, even in this case, if the entire bit 0 plane is deleted and the compression ratio becomes too high,
When the bit 0 plane is deleted from the bit plane corresponding to the high-frequency subband, the amount of calculation can be reduced and the compression ratio can be easily increased.

In the above description, the bit stream deletion method is limited for each of the resolution scalability and the SNR scalability. However, the present invention is not limited to this. Alternatively, in SNR scalability, it is also possible to delete in sub-band order. However, such a method requires a larger amount of calculation than the above-described method, and thus poses a problem particularly for a large image.

The image data compressed by the compression ratio changing unit 507 to the target compression ratio in this way is output from the image file output unit 508 to a storage device (not shown). When outputting the image to the network 506, the image may be fetched from the external storage device.

The DWT decoder 509 decodes the DWT-compressed image data, outputs the decoded image data to the image display unit 510, displays the image data, and confirms the contents. The DWT decoder 509 is the same as the one shown in FIG.
0 decoding device. Next, the image display unit 510
Will be described. Compression ratio changing unit 50
In the image from which the sign of the non-interest area has been completely deleted by 7,
In the non-interest area, what kind of pixel value is given becomes a problem. Here, when a doctor makes a diagnosis based on the X-ray image, a pixel value having a low luminance or a pixel value having a high density so that unnecessary light which may be the eyes of the doctor is not entered. Is output. For example, in FIG. 4A described above, the portion excluding the region of interest 402 from the irradiation region 401 is originally displayed in black, but when encoded, there is no pixel value information. , A low-luminance or high-density pixel value may be assigned.

On the other hand, when the image display unit 510 does not determine the pixel value of the non-interest area but completely deletes the bit stream corresponding to the non-interest area, the pixel value of the non-interest area is determined in advance. You can also create an image file that has been added.

The present invention can be applied to a system including a plurality of devices (for example, a host computer, an interface device, a reader, a printer, etc.), but can be applied to a single device (for example, a copier, a facsimile). Device).

Further, an object of the present invention is to supply a storage medium (or a recording medium) in which a program code of software for realizing the functions of the above-described embodiments is recorded to a system or an apparatus, and a computer (a computer) of the system or the apparatus. Alternatively, this can be achieved by a CPU or an MPU) reading and executing the program code stored in the storage medium. In this case, the program code itself read from the storage medium implements the functions of the above-described embodiment, and the storage medium storing the program code constitutes the present invention. By executing the program code read by the computer, not only the functions of the above-described embodiments are realized, but also an operating system (OS) running on the computer based on the instruction of the program code. This also includes a case where some or all of the actual processing is performed and the functions of the above-described embodiments are realized by the processing.

Further, after the program code read from the storage medium is written into the memory provided in the function expansion card inserted into the computer or the function expansion unit connected to the computer, the program code is read based on the instruction of the program code. This also includes the case where the CPU provided in the function expansion card or the function expansion unit performs part or all of the actual processing, and the processing realizes the functions of the above-described embodiments.

As described above, according to the present embodiment, there has been proposed an image processing method and apparatus capable of increasing the compression ratio of an image by a simple method for encoding using DWT transform. Although the present embodiment has been described using a case where a discrete wavelet transform is used for encoding, the present invention is not limited to this, and other orthogonal transforms and the like may be used. Further, the region of interest of the image may not be automatically detected, but may be instructed by, for example, an operator.

According to the present embodiment, the compression rate of the non-interest area in the image data is increased or the compression rate is increased by giving priority to deleting the code of the non-interest area. It has become possible to compress image data while preserving the image quality of the area preferentially.

Further, by displaying the pixels of the non-interest area in the X image with low luminance or high density, it becomes easy for a doctor or the like to pay attention to the area of interest, and diagnosis can be easily performed using the X-ray image. This has the effect.

[0131]

As described above, according to the present invention, it is possible to easily change the compression ratio of encoded image data to obtain image data having a desired compression ratio.

Further, according to the present invention, the non-interest area, or the code of the non-interest area and the interest area, which is a feature of the code by the DWT transform, is deleted in units of sub-bands or bit planes, thereby compressing the image data. The ratio can be changed to a desired compression ratio.

Further, according to the present invention, there is an effect that a code of a non-interest area of an image is preferentially deleted, so that the area of interest can be coded at a high compression rate with a low compression rate.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration of an image encoding device according to an embodiment of the present invention.

FIG. 2 is a diagram illustrating a configuration of a wavelet transform unit according to the present embodiment and subbands obtained by the transform.

FIG. 3 is a diagram illustrating conversion of a region of interest (designated region) in an image and bit shift of image data in the region.

FIG. 4 is a diagram illustrating an example of extracting a region of interest in an irradiation region of an X-ray image according to the present embodiment.

FIG. 5 is a diagram illustrating an example of extracting a region of interest in an irradiation region of an X-ray image according to the present embodiment.

FIG. 6 is a diagram illustrating an example of extracting a region of interest in an irradiation region of an X-ray image according to the present embodiment.

FIG. 7 is a diagram illustrating an operation of an entropy encoding unit according to the present embodiment.

FIG. 8 is a schematic diagram illustrating a configuration of a code string generated and output by spatial scalability.

FIG. 9 is a schematic diagram illustrating a configuration of a code string generated and output at the time of SNR scalability.

FIG. 10 is a block diagram illustrating a configuration of an image decoding device according to the present embodiment.

FIG. 11 is a diagram illustrating bit planes and an order of decoding for each bit plane by an entropy decoding unit according to the present embodiment.

FIG. 12 is a block diagram illustrating a configuration of a wavelet decoding unit according to the present embodiment.

FIG. 13 shows an example of a code string in the case of spatial scalability, each sub-band when decoding it, the size of an image displayed corresponding thereto, and the decoding of a code string of each sub-band. FIG. 9 is a diagram for explaining a change in a reproduced image accompanying the change.

FIG. 14 is a diagram illustrating an example of a code string in the case of SNR scalability and a decoding process thereof.

FIG. 15 is a block diagram illustrating a functional configuration of the image processing apparatus according to the embodiment of the present invention.

FIG. 16 is a flowchart showing an image compression rate update process in the image processing apparatus according to the embodiment of the present invention.

──────────────────────────────────────────────────続 き Continued on the front page (51) Int.Cl. ⁷ Identification symbol FI Theme coat ゛ (Reference) H04N 1/21 A61B 5/05 390 7/30 H04N 7/133 Z

Claims (21)

[Claims] An input unit for inputting an image file containing compressed image data; and a compression unit for deleting a code of a non-interest area in the image data input by the input unit to change a compression ratio of the image data. An image processing apparatus comprising: a rate changing unit. 2. The image processing apparatus according to claim 1, wherein the compression ratio changing unit changes a compression ratio of the image data according to a time factor. 3. An input unit for inputting an image file including compressed image data, and a code for changing a compression ratio of the image data by deleting a code of a non-interest area in the image data input by the input unit. 1 compression rate changing means, and second compression rate changing means for changing a compression rate of the image data by deleting a sign of a region of interest in the image data input by the input means. Image processing device. 4. A compression rate changed by the first or second compression rate changing means is determined based on attribute information of the image file, and when the image data is an X-ray image, The attribute information is at least any one of information on the type of the image, the imaging site, the number of days elapsed since the image capturing date, the number of days elapsed since the diagnosis date referred to the X-ray image, the number of days elapsed since the last access date, and the patient's visit state. The image processing apparatus according to claim 3, further comprising: 5. The image processing apparatus according to claim 3, wherein the first compression ratio changing unit deletes data of a low bit plane of the image data. 6. When the image data is resolution scalable coded, the second compression ratio changing means deletes bit plane data of a high-frequency subband, and converts the image data into an SNR scalable code. The image processing apparatus according to claim 3, wherein when the image data is converted, data of a low-level bit plane is deleted. 7. A region-of-interest extraction unit for extracting a region of interest of an input X-ray image, an image conversion unit for converting the X-ray image using a discrete wavelet transform, and a coefficient obtained by the image conversion unit Among them, a bit shift means for bit shifting up the value of the coefficient corresponding to the region of interest, and a compression means for compressing the coefficient shifted up by the bit shift means and the coefficient belonging to the non-interest area. 7. One of claims 3 to 6, characterized in that:
An image processing apparatus according to the item. 8. The apparatus according to claim 1, further comprising: a determination unit configured to determine whether to change the compression ratio based on the attribute information, wherein the first and second compression ratio change units determine whether or not the compression ratio is to be changed. The image processing apparatus according to claim 4, wherein the compression ratio is changed based on the compression ratio. 9. Decoding means for decoding image data of the image file, wherein a pixel value corresponding to the non-interest area of the image data decoded by the decoding means is output at low luminance or high density. 9. The image processing apparatus according to claim 3, further comprising output control means for displaying. 10. The region-of-interest extracting means, which inputs an X-ray image, extracts an irradiation region and a blank region of the X-ray image, sets the irradiation region as an entire image, and extracts the blank region from the entire image. The image processing apparatus according to claim 7, wherein a region from which is subtracted is extracted as a region of interest. 11. An input step of inputting an image file containing compressed image data, and a compression step of deleting a code of a non-interest area in the image data input in the input step to change a compression ratio of the image data. And a rate changing step. 12. The image processing method according to claim 11, wherein in the compression ratio changing step, a compression ratio of the image data is changed according to a temporal element. 13. An input step of inputting an image file including compressed image data, and a step of changing a compression ratio of the image data by deleting a code of a non-interest area in the image data input in the input step. (1) a compression ratio changing step of (1), and a second compression ratio changing step of changing a compression ratio of the image data by deleting a sign of a region of interest in the image data input in the input step. Image processing method. 14. The compression ratio changed in the first or second compression ratio changing step is determined based on attribute information of the image file, and when the image data is an X-ray image, The attribute information is at least any one of information on the type of the image, the imaging site, the number of days elapsed since the image capturing date, the number of days elapsed since the diagnosis date referred to the X-ray image, the number of days elapsed since the last access date, and the patient's visit state. 14. The image processing method according to claim 13, comprising: 15. The image processing method according to claim 13, wherein, in the first compression ratio changing step, data of a low bit plane of the image data is deleted. 16. In the second compression ratio changing step, when the image data has been subjected to resolution scalable coding, data of a high-frequency sub-band bit plane is deleted, and the image data is converted to an SNR scalable code. 15. The image processing method according to claim 13, wherein when the data is converted, data of a low-level bit plane is deleted. 17. A region of interest extraction step of extracting a region of interest of an input X-ray image, an image conversion step of converting the X-ray image using a discrete wavelet transform, A bit shifting step of shifting up the value of the coefficient corresponding to the region of interest, and a compression step of compressing the coefficient shifted up in the bit shifting step and the coefficient belonging to the non-interest region. A method according to any one of claims 13 to 16, wherein
The image processing method according to the item. 18. The method according to claim 18, further comprising: a determination step of determining whether to change the compression ratio based on the attribute information. The image processing method according to claim 14, wherein the compression ratio is changed based on the compression ratio. 19. A decoding step of decoding image data of the image file, wherein a pixel value corresponding to the non-interest area of the image data decoded in the decoding step is output at low luminance or high density. 19. The image processing method according to claim 13, further comprising an output control step of displaying. 20. In the region of interest extraction step, an X-ray image is input to extract an irradiation region and a blank region of the X-ray image, and the irradiation region is set as an entire image, and the blank region is extracted from the entire image. 18. The image processing method according to claim 17, wherein a region from which is subtracted is extracted as a region of interest. 21. A program for executing the image processing method according to claim 13.
Computer readable storage medium.