CN113473140A - Method, system, device and storage medium for lossy compression of cranial nerve images - Google Patents
Method, system, device and storage medium for lossy compression of cranial nerve images Download PDFInfo
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- 210000003792 cranial nerve Anatomy 0.000 title claims abstract description 73
- 238000000034 method Methods 0.000 title claims abstract description 49
- 238000004590 computer program Methods 0.000 claims description 7
- 230000006837 decompression Effects 0.000 abstract description 3
- 238000005516 engineering process Methods 0.000 description 4
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- 239000000463 material Substances 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 210000004556 brain Anatomy 0.000 description 1
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Abstract
The invention discloses a method, a system, equipment and a storage medium for lossy compression of a cranial nerve image. Meanwhile, compared with other lossy compression modes, the method has higher decompression speed and smaller computing resource consumption, thereby being suitable for computers with lower performance. The invention is convenient for researchers in the field of biomedicine to store and manage large-scale cranial nerve images.
Description
Technical Field
The present invention relates to the field of image compression technologies, and in particular, to a method, a system, a device, and a storage medium for lossy compression of a cranial nerve image.
Background
The basic format of the brain nerve image is the TIFF format, and compression methods for TIFF format images can be generally divided into lossless compression technology and lossy compression technology.
A common lossless compression technique is the LZW method. The method can compress the image to a lower size, and the decompressed image is consistent with the original image, thereby being a lossless compression technology. Because the method adopts a lossless coding algorithm and has no information screening and loss, the realized compression multiplying power is lower, and the compression effect on the cranial nerve images occupied by mass memory is still insufficient.
Common lossy compression techniques are JPEG2000 and JP3D methods. Both methods are lossy compression methods, i.e., compressed and decompressed images, have a portion of information lost compared to uncompressed images, but both methods achieve a much higher compression rate than lossless compression methods. The two methods have the disadvantages that the compression time is too long, the memory occupation of the computer in the compression process is too large, and a large amount of computing resources are consumed due to the complex algorithm.
Disclosure of Invention
The invention aims to provide a method, a system, equipment and a storage medium for lossy compression of a cranial nerve image, which can keep lower computing resource consumption and higher compression speed while achieving higher compression ratio.
The purpose of the invention is realized by the following technical scheme:
a method of lossy compression of a cranial nerve image, comprising:
judging whether the bit number of each cranial nerve image is not less than a set first threshold value or not;
if so, dividing the image according to the bit size to obtain a first part and a second part of the cranial nerve image, and respectively performing lossless compression and lossy compression on the first part and the second part; the lossless compression result and the lossy compression result are respectively used as frame data with the same serial number of the two video files, and then are stored as files with set formats by combining metadata for describing cranial nerve images;
if not, adopting lossy compression, taking the compression result as one frame of data of the video file, and storing the data as a file with a set format together with metadata for describing the cranial nerve image.
A system for lossy compression of cranial nerve images, comprising:
the bit number judging unit is used for judging whether the bit number of each cranial nerve image is not less than a set first threshold value or not;
the first lossy compression unit is used for obtaining a first part and a second part of the cranial nerve image by dividing according to the bit size when the bit number of the cranial nerve image is not less than a set first threshold value, and respectively carrying out lossless compression and lossy compression on the first part and the second part; the lossless compression result and the lossy compression result are respectively used as frame data with the same serial number of the two video files, and then are stored as files with set formats by combining metadata for describing cranial nerve images;
a second lossy compression unit, configured to, when the number of bits of the cranial nerve image is smaller than the set first threshold, perform lossy compression, use the compression result as one frame of data of the video file, and store the frame of data as a file in a set format in combination with metadata describing the cranial nerve image
A processing device, comprising: one or more processors; a memory for storing one or more programs;
wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the aforementioned methods.
A readable storage medium, storing a computer program, characterized in that the computer program realizes the aforementioned method when executed by a processor.
The technical scheme provided by the invention can be seen that the cranial nerve image can be compressed by hundreds of times, so that the occupied space of the cranial nerve image is greatly saved, and compared with the original image, the decompressed image does not lose too much visual information.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
Fig. 1 is a flowchart of a method for lossy compression of a cranial nerve image according to an embodiment of the present invention;
fig. 2 is a flowchart of lossy compression of a 16-bit encoded grayscale image according to an embodiment of the present invention;
fig. 3 is a schematic diagram of tree storage for nesting LAV files according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a lossy compression system for cranial nerve images according to an embodiment of the present invention;
fig. 5 is a schematic diagram of a processing apparatus according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
The terms that may be used herein are first described as follows:
the terms "comprising," "including," "containing," "having," or other similar terms of meaning should be construed as non-exclusive inclusions. For example: including a feature (e.g., material, component, ingredient, carrier, formulation, material, dimension, part, component, mechanism, device, process, procedure, method, reaction condition, processing condition, parameter, algorithm, signal, data, product, or article of manufacture), is to be construed as including not only the particular feature explicitly listed but also other features not explicitly listed as such which are known in the art.
The method for lossy compression of a cranial nerve image provided by the present invention is described in detail below. Details which are not described in detail in the embodiments of the invention belong to the prior art which is known to the person skilled in the art. Those not specifically mentioned in the examples of the present invention were carried out according to the conventional conditions in the art or conditions suggested by the manufacturer.
As shown in fig. 1, a flowchart of a method for lossy compression of a cranial nerve image according to an embodiment of the present invention mainly includes the following steps:
In the embodiment of the present invention, a preferred implementation of dividing by bit size includes: setting a second threshold value; the part which is not lower than the second threshold value is a high bit part and is called a first part; the part below the second threshold is a low bit part, referred to as a second part.
In the embodiment of the present invention, the lossless compression and the lossy compression include: lossless and lossy compression of HEVC.
And 3, if not, adopting lossy compression (the lossy compression of HEVC), taking a compression result as one frame of data of the video file, and storing the frame of data as a file with a set format together with metadata for describing the cranial nerve image.
In the embodiment of the present invention, the file with the set format includes: an LAV format file.
In the embodiment of the invention, in order to better perform storage management of the compressed file, the LAV format file adopts a nested tree-shaped storage mode; the LAV format file at the bottom layer includes two compressed video files and metadata (in the case of step 2) or one compressed video file and metadata (in the case of step 3), and the LAV format file at the upper layer includes the LAV format file at the lower layer and metadata describing the LAV format file at the lower layer.
Based on the scheme, LSMArch software based on Python language is compiled, the software calls FFMPEG (fast Fourier transform and motion Picture experts group) by using a program interface based on common FFMPEG (video processing software), and image processing is carried out by combining various video coding and decoding methods integrated by FFMPEG.
In order to more clearly show the technical solutions and the technical effects provided by the present invention, a method for lossy compression of a cranial nerve image according to an embodiment of the present invention is described in detail below with specific embodiments.
Considering that the acquisition of cranial nerve images is usually continuous, each image can be considered as each frame of the video. By utilizing the idea, a series of cranial nerve images are subjected to overall compression by utilizing a video compression method.
The invention also provides a thought of bit division in order to improve the compression ratio and simultaneously keep more information as much as possible because of adopting a lossy compression method. Illustratively, the first threshold is set to 16 and the second threshold is set to 6. For an image with a number of bits less than 16 (i.e. the case of step 3 mentioned above), for example, a typical 8-bit encoded gray scale image, the present invention will directly perform lossy compression on the whole in the HEVC encoding format. For an image with a number of bits not less than 16 (i.e. the aforementioned case of step 2), for example, a 16-bit coded grayscale image, the image is first divided into a high 6-bit portion (first portion) and a low 10-bit portion (second portion), and then the lossless compression method of HEVC is applied to the high-bit portion, and the lossy compression method of HEVC is applied to the low-bit portion. Converting a frame of data with the same sequence number in two video files as a compression result into a binary coding file, and storing the binary coding file and metadata which is defined by a user and describes the series of cranial nerve images into an LAV format file; as shown in fig. 2, a flow chart of lossy compression for a 16-bit encoded grayscale image.
In the embodiment of the invention, the lossy compression of the cranial nerve image can be realized by adopting a mode based on a CPU or a GPG; if the user has configured the GPU in the computer, the GPU can be used for more efficient compression, and a large amount of compression time is saved. When the lossy compression of the cranial nerve image is realized by adopting a CPU-based mode, the compression Rate is controlled by adopting a Constant Rate Factor (CRF) parameter; when the lossy compression of the cranial nerve image is realized by adopting a GPU-based mode, the compression rate is controlled by adopting constant quantizer parameters. Since different compression rates may be caused by the same parameter for different batches of cranial nerve images, a user may perform multiple compression attempts to select appropriate parameters to achieve a desired compression rate.
In the embodiment of the invention, the LAV file can be generated based on the HDF5 format file, and nested tree-shaped storage can be performed through a program, so that hierarchical management of the compressed file is realized. As shown in fig. 3, the lowest layer in the dashed box is the lowest-level LAV file obtained by compression, and these LAV files contain the compressed images obtained by the foregoing method and metadata describing these images (i.e., data shown below the dashed box). Each LAV file needs to be converted into a binary format when nested for storage, so that the LAV file at the upper layer contains a plurality of LAV files at the lowest level and metadata describing the LAV files. The top layer is the LAV file of the highest hierarchy, and also comprises a plurality of LAV files of lower hierarchies and metadata. The storage management format conforms to the classification idea of the cranial nerve image, namely, the cranial nerve image of a larger area is composed of a plurality of images of small areas.
In the embodiment of the present invention, the metadata corresponding to the LAV file at the lowest level includes the size of the compressed image, the bit depth of the image, the CRF parameter value selected during compression, the bit division mode (i.e. the second threshold) during compression, and the compression rate achieved after compression; and some parameters internal to the software as interfaces; metadata corresponding to the high-level LAV files generally records the hierarchical structure of an LAV file tree, namely the node relation of all the lower-level LAV files when the current LAV files are taken as root nodes of the tree; there are also parameters that act as interfaces within the software.
Based on the tree-like storage structure, an embodiment of the present invention further provides a fast decompression method, including the steps of: decompressing from the LAV format file at the top layer, decomposing into a plurality of LAV format files at the lower layer until decomposing into the LAV format file at the bottom layer; decomposing the video files into the files in the LAV format at the bottom layer to obtain two video files and corresponding metadata; reading each frame of the two videos to obtain two images corresponding to the first part and the second part of each cranial nerve image, and shifting and splicing the two images to obtain the finally decompressed cranial nerve image. Or decomposing the video file into a bottommost LAV format file to obtain a video file and corresponding metadata; reading each frame of the video to obtain a corresponding cranial nerve image.
Although the invention belongs to lossy compression, under the condition of proper parameter selection, the finally decompressed image is slightly different from the original image in vision.
By adopting the scheme of the embodiment of the invention, the cranial nerve image can be compressed by hundreds of times, the occupied space of the cranial nerve image is greatly saved, and compared with the original image, the decompressed image does not lose too much visual information. Meanwhile, compared with other lossy compression modes, the method has higher decompression speed and smaller computing resource consumption, thereby being suitable for computers with lower performance. The invention is convenient for researchers in the field of biomedicine to store and manage large-scale cranial nerve images.
Another embodiment of the present invention further provides a system for lossy compression of a cranial nerve image, which is mainly used for implementing the method provided in the foregoing embodiment, as shown in fig. 4, the system mainly includes:
the bit number judging unit is used for judging whether the bit number of each cranial nerve image is not less than a set first threshold value or not;
the first lossy compression unit is used for obtaining a first part and a second part of the cranial nerve image by dividing according to the bit size when the bit number of the cranial nerve image is not less than a set first threshold value, and respectively carrying out lossless compression and lossy compression on the first part and the second part; the lossless compression result and the lossy compression result are respectively used as frame data with the same serial number of the two video files, and then are stored as files with set formats by combining metadata for describing cranial nerve images;
and the second lossy compression unit is used for adopting lossy compression when the bit number of the cranial nerve image is less than the set first threshold value, taking the compression result as one frame of data of the video file, and storing the data as a file with a set format together with metadata for describing the cranial nerve image.
Another embodiment of the present invention further provides a processing apparatus, as shown in fig. 5, which mainly includes: one or more processors; a memory for storing one or more programs; wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the methods provided by the foregoing embodiments.
Further, the processing device further comprises at least one input device and at least one output device; in the processing device, a processor, a memory, an input device and an output device are connected through a bus.
In the embodiment of the present invention, the specific types of the memory, the input device, and the output device are not limited; for example:
the input device can be a touch screen, an image acquisition device, a physical button or a mouse and the like;
the output device may be a display terminal;
the Memory may be a Random Access Memory (RAM) or a non-volatile Memory (non-volatile Memory), such as a disk Memory.
Another embodiment of the present invention further provides a readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the method provided by the foregoing embodiment.
The readable storage medium in the embodiment of the present invention may be provided in the foregoing processing device as a computer readable storage medium, for example, as a memory in the processing device. The readable storage medium may be various media that can store program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disk.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A method for lossy compression of a cranial nerve image, comprising:
judging whether the bit number of each cranial nerve image is not less than a set first threshold value or not;
if so, dividing the image according to the bit size to obtain a first part and a second part of the cranial nerve image, and respectively performing lossless compression and lossy compression on the first part and the second part; the lossless compression result and the lossy compression result are respectively used as frame data with the same serial number of the two video files, and then are stored as files with set formats by combining metadata for describing cranial nerve images;
if not, adopting lossy compression, taking the compression result as one frame of data of the video file, and storing the data as a file with a set format together with metadata for describing the cranial nerve image.
2. The method of claim 1, wherein the dividing into the first part and the second part of the cranial nerve image by the bit size comprises:
setting a second threshold value; the part which is not lower than the second threshold value is a high bit part and is called a first part; the part below the second threshold is a low bit part, referred to as a second part.
3. The method of claim 1, wherein the lossless compression and the lossy compression comprise: lossless and lossy compression of HEVC.
4. The method of claim 1, wherein the formatted file comprises: an LAV format file.
5. The method according to claim 4, wherein the LAV format file is stored in a nested tree format; the LAV format file at the bottom layer includes two compressed video files and metadata or a compressed video file and source data, and the LAV format file at the upper layer includes an LAV format file at the lower layer and metadata describing the LAV format file at the lower layer.
6. The method of claim 5, further comprising the step of decompressing, the method comprising:
decompressing from the LAV format file at the top layer, decomposing into a plurality of LAV format files at the lower layer until decomposing into the LAV format file at the bottom layer;
decomposing the video files into the files in the LAV format at the bottom layer to obtain two video files and corresponding metadata; reading each frame of the two videos to obtain two images corresponding to a first part and a second part of each cranial nerve image, and shifting and splicing the two images to obtain a finally decompressed cranial nerve image; or decomposing the video file into a bottommost LAV format file to obtain a video file and corresponding metadata; reading each frame of the video to obtain a corresponding cranial nerve image.
7. The method for lossy compression of an image of cranial nerves according to any of claims 1 to 6, further comprising: realizing the lossy compression of the cranial nerve image by adopting a mode based on a CPU or GPG;
when the lossy compression of the cranial nerve image is realized by adopting a CPU-based mode, the compression rate is controlled by adopting a constant rate factor parameter;
when the lossy compression of the cranial nerve image is realized by adopting a GPU-based mode, the compression rate is controlled by adopting constant quantizer parameters.
8. A system for lossy compression of cranial nerve images, comprising:
the bit number judging unit is used for judging whether the bit number of each cranial nerve image is not less than a set first threshold value or not;
the first lossy compression unit is used for obtaining a first part and a second part of the cranial nerve image by dividing according to the bit size when the bit number of the cranial nerve image is not less than a set first threshold value, and respectively carrying out lossless compression and lossy compression on the first part and the second part; the lossless compression result and the lossy compression result are respectively used as frame data with the same serial number of the two video files, and then are stored as files with set formats by combining metadata for describing cranial nerve images;
and the second lossy compression unit is used for adopting lossy compression when the bit number of the cranial nerve image is less than the set first threshold value, taking the compression result as one frame of data of the video file, and storing the data as a file with a set format together with metadata for describing the cranial nerve image.
9. A processing device, comprising: one or more processors; a memory for storing one or more programs;
wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-7.
10. A readable storage medium, storing a computer program, characterized in that the computer program, when executed by a processor, implements the method according to any of claims 1 to 7.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114466195A (en) * | 2021-12-29 | 2022-05-10 | 航天科工网络信息发展有限公司 | Image transmission method and device based on SPICE protocol |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004254131A (en) * | 2003-02-20 | 2004-09-09 | Ricoh Co Ltd | Image compression apparatus, image processing apparatus, image expansion apparatus, image compression method, image processing method, image expansion method, program, and recording medium |
| US20050165796A1 (en) * | 2004-01-15 | 2005-07-28 | Xerox Corporation. | Method and system for managing image files in a hierarchical storage mangement system |
| US20130251256A1 (en) * | 2012-03-21 | 2013-09-26 | Canon Kabushiki Kaisha | Image compression |
| CN104699826A (en) * | 2014-06-10 | 2015-06-10 | 霍亮 | Pyramid layer-based storage method and spatial database system for image data |
| US20180160013A1 (en) * | 2016-12-07 | 2018-06-07 | Xerox Corporation | System and method for adaptively compressing data having noisy images using lossless compression |
| CN108254724A (en) * | 2018-01-26 | 2018-07-06 | 西安电子科技大学 | Improve the SAR data compressibility and method of compression quality BAQ |
| CN112612830A (en) * | 2020-12-03 | 2021-04-06 | 海光信息技术股份有限公司 | Method and system for exporting compressed data in batches and electronic equipment |
-
2021
- 2021-07-15 CN CN202110799286.4A patent/CN113473140B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004254131A (en) * | 2003-02-20 | 2004-09-09 | Ricoh Co Ltd | Image compression apparatus, image processing apparatus, image expansion apparatus, image compression method, image processing method, image expansion method, program, and recording medium |
| US20050165796A1 (en) * | 2004-01-15 | 2005-07-28 | Xerox Corporation. | Method and system for managing image files in a hierarchical storage mangement system |
| US20130251256A1 (en) * | 2012-03-21 | 2013-09-26 | Canon Kabushiki Kaisha | Image compression |
| CN104699826A (en) * | 2014-06-10 | 2015-06-10 | 霍亮 | Pyramid layer-based storage method and spatial database system for image data |
| US20180160013A1 (en) * | 2016-12-07 | 2018-06-07 | Xerox Corporation | System and method for adaptively compressing data having noisy images using lossless compression |
| CN108254724A (en) * | 2018-01-26 | 2018-07-06 | 西安电子科技大学 | Improve the SAR data compressibility and method of compression quality BAQ |
| CN112612830A (en) * | 2020-12-03 | 2021-04-06 | 海光信息技术股份有限公司 | Method and system for exporting compressed data in batches and electronic equipment |
Non-Patent Citations (5)
| Title |
|---|
| ANDRÉ F.R. GUARDA: "A method to improve HEVC lossless coding of volumetric medical images", SIGNAL PROCESSING: IMAGE COMMUNICATION * |
| M LAROBINA: "Medical image file formats", JOURNAL OF DIGITAL IMAGING * |
| 严小红: "论数字图象压缩算法研究与实现", 滁州职业技术学院学报 * |
| 徐妮妮;李晨光;: "基于JPEG标准的16bit图像有损压缩应用", 电信科学, no. 04 * |
| 李元祥: "MODIS多光谱图像压缩研究", 电子与信息学报 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114466195A (en) * | 2021-12-29 | 2022-05-10 | 航天科工网络信息发展有限公司 | Image transmission method and device based on SPICE protocol |
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