CN113473140B - Lossy compression method, system, device and storage medium for cranial nerve image - Google Patents
Lossy compression method, system, device and storage medium for cranial nerve image Download PDFInfo
- Publication number
- CN113473140B CN113473140B CN202110799286.4A CN202110799286A CN113473140B CN 113473140 B CN113473140 B CN 113473140B CN 202110799286 A CN202110799286 A CN 202110799286A CN 113473140 B CN113473140 B CN 113473140B
- Authority
- CN
- China
- Prior art keywords
- cranial nerve
- lossy compression
- compression
- file
- nerve image
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000007906 compression Methods 0.000 title claims abstract description 123
- 230000006835 compression Effects 0.000 title claims abstract description 122
- 210000003792 cranial nerve Anatomy 0.000 title claims abstract description 71
- 238000000034 method Methods 0.000 title claims abstract description 49
- 230000006837 decompression Effects 0.000 claims abstract description 4
- 238000004590 computer program Methods 0.000 claims description 5
- 210000004556 brain Anatomy 0.000 claims 3
- 210000005036 nerve Anatomy 0.000 claims 3
- 230000005484 gravity Effects 0.000 claims 1
- 238000004364 calculation method Methods 0.000 abstract description 3
- 238000004422 calculation algorithm Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- -1 carrier Substances 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 239000000306 component Substances 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 239000004615 ingredient Substances 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000007858 starting material Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
- H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
- H04N19/172—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a picture, frame or field
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/42—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by implementation details or hardware specially adapted for video compression or decompression, e.g. dedicated software implementation
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/70—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by syntax aspects related to video coding, e.g. related to compression standards
Abstract
The invention discloses a lossy compression method, a lossy compression system, lossy compression equipment and a lossy compression storage medium for a cranial nerve image. Meanwhile, compared with other lossy compression modes, the method has the advantages of faster decompression speed and smaller calculation resource consumption, and is also suitable for computers with lower performance. The invention is convenient for researchers in the biomedical field 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, an apparatus, and a storage medium for lossy compression of a cranial nerve image.
Background
The basic format of the cranial nerve image is a TIFF format, and compression modes for TIFF format images can be generally classified into lossless compression techniques and lossy compression techniques.
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, so that the method is a lossless compression technology. Because the method adopts a lossless coding algorithm, no information is screened and lost, the compression multiplying power can be lower, and the compression effect on the cranial nerve image occupied by a mass memory is still insufficient.
Common lossy compression techniques are the JPEG2000 and JP3D methods. Both methods are lossy compression methods, i.e. the compressed and decompressed image has a part of the information lost compared to the uncompressed image, but at the same time the compression rate achieved by both methods is much higher than by the lossless compression method. The two methods have the defects of overlong compression time and overlarge memory occupation of a computer in the compression process, and a large amount of calculation resources are consumed because of complex algorithm.
Disclosure of Invention
The invention aims to provide a lossy compression method, a lossy compression system, lossy compression equipment and a lossy compression storage medium for a cranial nerve image, which can achieve a higher compression rate, and simultaneously can keep lower consumption of computing resources and higher compression speed.
The invention aims at realizing 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;
if yes, dividing the size of the bit to obtain a first part and a second part of the cranial nerve image, and performing lossless compression and lossy compression on the first part and the second part respectively; the lossless compression and the lossy compression result are respectively used as a frame of data with the same serial number of two video files, and then are stored as files in a set format together with metadata for describing the cranial nerve image;
if not, adopting lossy compression, taking the compression result as one frame of data of the video file, and storing the video file as a file in a set format together with metadata for describing the cranial nerve image.
A lossy compression system of a cranial nerve image, comprising:
a bit number judging unit for judging, for each cranial nerve image, whether or not the bit number thereof is not less than a set first threshold;
the first lossy compression unit is used for dividing the size of the bit to obtain a first part and a second part of the cranial nerve image when the bit number of the cranial nerve image is not less than a set first threshold value, and performing lossless compression and lossy compression on the first part and the second part respectively; the lossless compression and the lossy compression result are respectively used as a frame of data with the same serial number of two video files, and then are stored as files in a set format together with metadata for describing the cranial nerve image;
a second lossy compression unit for storing the compression result as one frame of data of the video file as a file in a set format together with metadata describing the cranial nerve image by lossy compression when the bit number of the cranial nerve image is smaller than a set first threshold
A processing apparatus, 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 aforementioned method is implemented when the computer program is executed by a processor.
According to the technical scheme provided by the invention, the cranial nerve image can be compressed to hundreds of times, the occupied space of the cranial nerve image is greatly saved, and compared with the original image, the decompressed image has no loss of excessive visual information.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a lossy compression method of a cranial nerve image according to an embodiment of the present invention;
FIG. 2 is a lossy compression flow chart of a 16-bit encoded grayscale image provided by an embodiment of the invention;
FIG. 3 is a schematic diagram of tree-like storage of nested 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 following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to fall within the scope of the invention.
The terms that may be used herein will first be described as follows:
the terms "comprises," "comprising," "includes," "including," "has," "having" or other similar referents are to be construed to cover a non-exclusive inclusion. For example: including a particular feature (e.g., a starting material, component, ingredient, carrier, formulation, material, dimension, part, means, mechanism, apparatus, step, procedure, method, reaction condition, processing condition, parameter, algorithm, signal, data, product or article of manufacture, etc.), should be construed as including not only a particular feature but also other features known in the art that are not explicitly recited.
The following describes a method for lossy compression of a cranial nerve image according to the present invention. What is not described in detail in the embodiments of the present invention belongs to the prior art known to those skilled in the art. The specific conditions are not noted in the examples of the present invention and are carried out according to the conditions conventional in the art or suggested by the manufacturer.
As shown in fig. 1, a flowchart of a lossy compression method for a cranial nerve image according to an embodiment of the present invention mainly includes the following steps:
and step 1, judging whether the bit number of each cranial nerve image is not smaller than a set first threshold value.
Step 2, if yes, dividing the size of the bit to obtain a first part and a second part of the cranial nerve image, and performing lossless compression and lossy compression on the first part and the second part respectively; the lossless compression and the lossy compression result are respectively used as one frame of data with the same serial number of two video files, and are stored as files in a set format together with metadata for describing the cranial nerve image.
In the embodiment of the present invention, a preferred implementation of the division by the bit size includes: setting a second threshold; the part not lower than the second threshold is a high-bit part, called a first part; the portion below the second threshold is the low bit portion, referred to as the second portion.
In an embodiment of the present invention, the lossless compression and the lossy compression include: lossless compression and lossy compression of HEVC.
And 3, if not, adopting lossy compression (HEVC lossy compression), taking a compression result as one frame of data of a video file, and storing the video file as a file in a set format together with metadata for describing the cranial nerve image.
In an 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 contains 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 contains the LAV format file at the lower layer and metadata describing the LAV format file at the lower layer.
Based on the scheme, the invention writes LSMArch software based on Python language, the software is based on common video processing software FFMPEG, and uses a program interface to call FFMPEG, and combines various video coding and decoding methods of FFMPEG integration to process images.
In order to more clearly show the technical scheme and the technical effects provided by the invention, a detailed description of a lossy compression method for a cranial nerve image provided by the embodiment of the invention is provided below.
Considering that the acquisition of cranial nerve images is typically continuous, each image can be considered as each frame of video. By utilizing the idea, a series of cranial nerve images are integrally compressed by utilizing a video compression method.
The invention also provides a bit division idea in order to keep more information as much as possible while improving the compression rate because the invention adopts a lossy compression method. Illustratively, the first threshold is set to 16 and the second threshold is set to 6. For images with a number of bits less than 16 (i.e. in the case of step 3 mentioned earlier), for example, a typical 8-bit coded gray scale image, the present invention will directly perform lossy compression on the whole using the HEVC coding format. For an image with a number of bits not less than 16 (i.e. in the case of the aforementioned step 2), for example, a 16-bit coded gray scale image, the image is first divided into a high 6-bit portion (first portion) and a low 10-bit portion (second portion), then a lossless compression mode of HEVC is used for the high-bit portion, and a lossy compression mode of HEVC is used for the low-bit portion. The compressed result is used as one frame of data with the same serial number in two video files, is converted into a binary coded file, and is stored into an LAV format file together with metadata which is defined by a user and describes the series of cranial nerve images; as shown in fig. 2, is a lossy compression flow chart of a 16-bit encoded gray scale image.
In the embodiment of the invention, the lossy compression of the cranial nerve image can be realized in a mode based on a CPU or GPG; if the GPU is configured in the computer of the user, 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 in a CPU-based manner, the compression rate is controlled by adopting constant rate factor (Constant Rate Factor, CRF) parameters; when lossy compression of the cranial nerve image is achieved using a GPU-based approach, the compression rate is controlled using a constant quantizer parameter. Since the same parameter may result in different compression rates for different batches of cranial nerve images, the user may perform multiple compression attempts to select the appropriate parameters to achieve the desired compression rate.
In the embodiment of the invention, the LAV file can be generated based on the HDF5 format file, and the hierarchical management of the compressed file can be realized by performing nested tree-like storage through a program. 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 include the compressed images obtained by the foregoing method and metadata describing these images (i.e., the 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 of the upper layer contains a plurality of LAV files of the lowest hierarchy and metadata describing the LAV files. The top layer is the highest-level LAV file, and also contains a plurality of lower-level LAV files and metadata. The storage management format accords with the hierarchical thought of the cranial nerve image, namely, the cranial nerve image of a larger area is composed of images of a plurality of small areas.
In the embodiment of the invention, metadata corresponding to the lowest-level LAV file comprises the size of a compressed image, the bit depth of the image, a CRF parameter value selected during compression, a bit division mode (namely a second threshold value) 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 the LAV file tree, namely, when the current LAV file is taken as the root node of the tree, the node relation of all the LAV files at the lower layer; there are also some parameters that are internal to the software as interfaces.
Based on the tree-like storage structure, the embodiment of the invention also provides a fast decompression method, which comprises the following steps: decompressing from the top LAV format file to a plurality of lower LAV format files until the bottom LAV format file is decomposed; decomposing the file into the LAV format file at the bottommost layer to obtain two video files and corresponding metadata; and 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 a final decompressed cranial nerve image. Or decomposing the file into the LAV format file at the bottommost layer to obtain a video file and corresponding metadata; and reading each frame of the video to obtain a corresponding cranial nerve image.
Although the invention pertains to lossy compression, the resulting image is visually less image-wise than the original image, with appropriate choice of parameters.
By adopting the scheme provided by the embodiment of the invention, the cranial nerve image can be compressed to hundreds of times, the occupied space of the cranial nerve image is greatly saved, and compared with the original image, the decompressed image has no loss of excessive visual information. Meanwhile, compared with other lossy compression modes, the method has the advantages of faster decompression speed and smaller calculation resource consumption, and is also suitable for computers with lower performance. The invention is convenient for researchers in the biomedical field to store and manage large-scale cranial nerve images.
Another embodiment of the present invention further provides a lossy compression system for cranial nerve images, which is mainly used for implementing the method provided in the foregoing embodiment, as shown in fig. 4, and the system mainly includes:
a bit number judging unit for judging, for each cranial nerve image, whether or not the bit number thereof is not less than a set first threshold;
the first lossy compression unit is used for dividing the size of the bit to obtain a first part and a second part of the cranial nerve image when the bit number of the cranial nerve image is not less than a set first threshold value, and performing lossless compression and lossy compression on the first part and the second part respectively; the lossless compression and the lossy compression result are respectively used as a frame of data with the same serial number of two video files, and then are stored as files in a set format together with metadata for describing the cranial nerve image;
and the second lossy compression unit is used for adopting lossy compression when the bit number of the cranial nerve image is smaller than a set first threshold value, taking a compression result as one frame of data of the video file, and storing the compression result as a file in a set format together with metadata for describing the cranial nerve image.
Another embodiment of the present invention also 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, the processor, the memory, the input device and the output device are connected through buses.
In the embodiment of the 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 key or a mouse and the like;
the output device may be a display terminal;
the memory may be random access memory (Random Access Memory, RAM) or non-volatile memory (non-volatile memory), such as disk memory.
Another embodiment of the present invention also provides a readable storage medium storing a computer program which, when executed by a processor, implements the method provided by the foregoing embodiment.
The readable storage medium according to the embodiment of the present invention may be provided as a computer readable storage medium in the aforementioned processing apparatus, for example, as a memory in the processing apparatus. The readable storage medium may be any of various media capable of storing a program code, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, and an optical disk.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions easily contemplated by those skilled in the art within the scope of the present invention should be included in the scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.
Claims (7)
1. 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;
if yes, dividing the ratio of the first part to the second part to obtain a first part and a second part of the cranial nerve image, and performing lossless compression and lossy compression on the first part and the second part respectively; the lossless compression and the lossy compression result are respectively used as a frame of data with the same serial number of two video files, and then are stored as files in a set format together with metadata for describing the cranial nerve image;
if not, adopting lossy compression, taking the compression result as one frame of data of a video file, and storing the video file as a file in a set format by combining metadata for describing the cranial nerve image;
the file with the set format comprises: the LAV format file is generated based on the HDF5 format file; the LAV format file adopts a nested tree-shaped storage mode; the LAV format file at the bottom layer comprises two compressed video files and metadata or one compressed video file and source data, and the LAV format file at the upper layer comprises the LAV format file at the lower layer and the metadata describing the LAV format file at the lower layer;
the method further comprises a step of decompression, comprising:
decompressing from the top LAV format file to a plurality of lower LAV format files until the bottom LAV format file is decomposed;
decomposing the file into the LAV format file at the bottommost 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 final decompressed cranial nerve image; or decomposing the file into the LAV format file at the bottommost layer to obtain a video file and corresponding metadata; and reading each frame of the video to obtain a corresponding cranial nerve image.
2. The method of claim 1, wherein the dividing by specific gravity to obtain the first portion and the second portion of the cranial nerve image comprises:
setting a second threshold; the part not lower than the second threshold is a high-bit part, called a first part; the portion below the second threshold is the low bit portion, referred to as the second portion.
3. The method of lossy compression of a cranial nerve image according to claim 1, wherein the lossless compression and lossy compression include: lossless compression and lossy compression of HEVC.
4. A method of lossy compression of a cranial nerve image according to any one of claims 1 to 3, wherein the method further comprises: the method comprises the steps of realizing lossy compression of a 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 constant rate factor parameters;
when lossy compression of the cranial nerve image is achieved using a GPU-based approach, the compression rate is controlled using a constant quantizer parameter.
5. A lossy compression system for images of the brain nerve, characterized in that it is adapted to implement the method according to any one of claims 1 to 4, comprising:
a bit number judging unit for judging, for each cranial nerve image, whether or not the bit number thereof is not less than a set first threshold;
the first lossy compression unit is used for dividing the brain nerve image into a first part and a second part according to the ratio of the extra-high to the low when the bit number of the brain nerve image is not less than a set first threshold value, and performing lossless compression and lossy compression on the first part and the second part respectively; the lossless compression and the lossy compression result are respectively used as a frame of data with the same serial number of two video files, and then are stored as files in a set format together with metadata for describing the cranial nerve image;
and the second lossy compression unit is used for adopting lossy compression when the bit number of the cranial nerve image is smaller than a set first threshold value, taking a compression result as one frame of data of the video file, and storing the compression result as a file in a set format together with metadata for describing the cranial nerve image.
6. A processing apparatus, 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 1-4.
7. A readable storage medium storing a computer program, characterized in that the method according to any one of claims 1-4 is implemented when the computer program is executed by a processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110799286.4A CN113473140B (en) | 2021-07-15 | 2021-07-15 | Lossy compression method, system, device and storage medium for cranial nerve image |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110799286.4A CN113473140B (en) | 2021-07-15 | 2021-07-15 | Lossy compression method, system, device and storage medium for cranial nerve image |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113473140A CN113473140A (en) | 2021-10-01 |
| CN113473140B true CN113473140B (en) | 2024-02-23 |
Family
ID=77880426
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110799286.4A Active CN113473140B (en) | 2021-07-15 | 2021-07-15 | Lossy compression method, system, device and storage medium for cranial nerve image |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113473140B (en) |
Families Citing this family (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 |
Citations (4)
| 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 |
| CN104699826A (en) * | 2014-06-10 | 2015-06-10 | 霍亮 | Pyramid layer-based storage method and spatial database system for image data |
| 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 |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7836021B2 (en) * | 2004-01-15 | 2010-11-16 | Xerox Corporation | Method and system for managing image files in a hierarchical storage management system |
| AU2012201684A1 (en) * | 2012-03-21 | 2013-10-10 | Canon Kabushiki Kaisha | Image compression |
| US10158784B2 (en) * | 2016-12-07 | 2018-12-18 | Xerox Corporation | System and method for adaptively compressing data having noisy images using lossless compression |
-
2021
- 2021-07-15 CN CN202110799286.4A patent/CN113473140B/en active Active
Patent Citations (4)
| 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 |
| CN104699826A (en) * | 2014-06-10 | 2015-06-10 | 霍亮 | Pyramid layer-based storage method and spatial database system for image data |
| 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 |
|---|
| A method to improve HEVC lossless coding of volumetric medical images;André F.R. Guarda;Signal Processing: Image Communication;全文 * |
| Medical image file formats;M Larobina;journal of digital imaging;全文 * |
| MODIS多光谱图像压缩研究;李元祥;电子与信息学报;全文 * |
| 基于JPEG标准的16bit图像有损压缩应用;徐妮妮;李晨光;;电信科学(04);全文 * |
| 论数字图象压缩算法研究与实现;严小红;滁州职业技术学院学报;全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113473140A (en) | 2021-10-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| EP0777386B1 (en) | Method and apparatus for encoding and decoding an image | |
| US20140241630A1 (en) | Indexed Color History In Image Coding | |
| CN107483059B (en) | Multi-channel data coding and decoding method and device based on dynamic Huffman tree | |
| US8948530B2 (en) | Adaptive image compression system and method | |
| CN113795870B (en) | Method, device and storage medium for encoding and decoding point cloud attribute | |
| CN113473140B (en) | Lossy compression method, system, device and storage medium for cranial nerve image | |
| CN111241344B (en) | Video duplicate checking method, system, server and storage medium | |
| CN111726615B (en) | Point cloud coding and decoding method and coder-decoder | |
| US8928660B2 (en) | Progressive mesh decoding apparatus and method | |
| KR100439371B1 (en) | Multimedia searching method using histogram | |
| JP2006262161A (en) | Image processor, image processing method, and storage medium with the method stored therein | |
| JP2006238036A (en) | Computer graphic data encoding device, decoding device, encoding method, and decoding method | |
| JP2885433B2 (en) | Image processing method and apparatus | |
| JP2020123917A (en) | Image processing program, image processing device, and image processing method | |
| JP2020053820A (en) | Quantization and encoder creation method, compressor creation method, compressor creation apparatus, and program | |
| US8582906B2 (en) | Image data compression and decompression | |
| WO2021010200A1 (en) | Information processing device and method | |
| US7142235B2 (en) | Opportunistic improvement of digital camera image quality | |
| CN113422965A (en) | Image compression method and device based on generation countermeasure network | |
| JP4462360B2 (en) | Image compression apparatus and image expansion apparatus | |
| WO2007099327A2 (en) | Data compression | |
| Matos et al. | Lossy-to-lossless compression of biomedical images based on image decomposition | |
| JP2004253889A (en) | Image processing apparatus and method | |
| JP2024512731A (en) | Image processing method, system, encoder, computer readable storage medium | |
| US8260070B1 (en) | Method and system to generate a compressed image utilizing custom probability tables |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |