Band reordering heuristics for lossless satellite image compression with 3D-CALIC and CCSDS

Afjal, Masud Ibn; Mamun, Md. Al; Uddin, Md. Palash

doi:10.1016/j.jvcir.2019.01.042

Cited by 47 publications

(10 citation statements)

References 21 publications

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“…JPEG-LS is a lossless or near lossless compression standard for continuous-tone image proposed by the International Standards Organization ISO/IEC JTC1 [28,29], it is based on the LOCO-I algorithm (low complexity lossless compression for images) which depends on a pixel prediction based contextual statistical model [30]. It has been widely used for image compression and image security [31,32].…”

Section: Jpeg-ls-based Image Codingmentioning

confidence: 99%

A secure lossless recovery for medical images based on image encoding and data self-embedding

Gao

2021

Cluster Comput

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To protect the security of data outsourced to the cloud, the tampers detection and recovery for outsourced image have aroused the concern of people. A secure tampering detection and lossless recovery for medical images (MI) using permutation ordered binary (POB) number system is proposed. In the proposed scheme, the region of interest (ROI) of MI is first extracted, and then, ROI is divided into some no-overlapping blocks, and image encoding is conducted on these blocks based on the better compression performance of JPEG-LS for medical image. After that, the generated compression data by all the blocks are divided into high 4-bit and low 4-bit planes, and shuffling and combination are used to generate two plane images. Owing to the substantial redundancies space in the compressed data, the data of each plane are spread to the size of the original image. Lastly, authentication data of two bits is obtained for every pixel and inserted into the pixel itself within the each plane, and the corresponding 10-bit data is transformed into the POB value of 8-bit. Furthermore, encryption is implemented on the above image to produce two shares which can be outsourced to the cloud server. The users can detect tampered part and recover original image when they down load the shares from the cloud. Extensive experiments on some ordinary medical image and COVID-19 image datasets show that the proposed approach can locate the tampered parts within the MI, and the original MI can be recovered without any loss even if one of the shares are totally destroyed, or two shares are tampered at the ration not more than 50%. Some comparisons and analysis are given to show the better performance of the scheme.

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Section: Jpeg-ls-based Image Codingmentioning

confidence: 99%

A secure lossless recovery for medical images based on image encoding and data self-embedding

Gao

2021

Cluster Comput

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“…Afjal et al 49 Decreases the computational complexity involved in selection of optimal bands for different predictive compression.…”

Section: Lstm-rnn 47mentioning

confidence: 99%

“…RWA-C 24 already discussed in transformation-based technique can be classified in this category. Afjal et al 49 evaluated the effect of band reordering on context-based adaptive lossless image coder and lossless CCSDS prediction-based compression algorithm. Band reordering is the technique that rearranges the band sequence in the image to be compressed to code good predictor bands first that will affect the prediction of later bands.…”

Section: Cang and Wang 51mentioning

confidence: 99%

Comprehensive review of hyperspectral image compression algorithms

2020

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Rapid advancement in the development of hyperspectral image analysis techniques has led to specialized hyperspectral missions. It results in the bulk transmission of hyperspectral images from sensors to analysis centers and finally to data centers. Storage of these large size images is a critical issue that is handled by compression techniques. This survey focuses on different hyperspectral image compression algorithms that have been classified into two broad categories based on eight internal and six external parameters. In addition, we identified research challenges and suggested future scope for each technique. The detailed classification used in this paper can categorize other compression algorithms and may help in selecting research objectives.

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“…Image compression algorithms can adopt limited storage space to save a larger amount of image data, which can effectively reduce the images data size of the same quality. Therefore, some watermarking schemes based on compression are proposed [1,3,5,15]. The scheme [3] presented an intelligent model based on reversible watermarking techniques.…”

Section: Introductionmentioning

confidence: 99%

Medical images lossless recovery based on POB number system and image compression

Zhang

et al. 2022

Multimed Tools Appl

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To protect the information integrity of the medical images, this paper proposes a secure lossless recovery scheme for medical images based on image block compression and permutation ordered binary (POB) number system, which includes two parts: share generation, and lossless recovery. In the shares generation stage, the region of interest (ROI) of the original medical image and the image block compression coding algorithm JPEG-LS, are firstly adopted to generate the compressed data, which can use limited storage space to place the data repeatedly. Then, after separating the bit-plane, the compressed data are executed by data reorganization and data encryption respectively on the high-plane and the low-plane. Finally, two authentication bits are extracted by 8-bit pixel of two planes to be inserted into the pixel itself, and then the 10-bit pixel is converted into an 8-bit POB value to produce two shares of ShareH and ShareL, respectively. In the lossless recovery stage, data of placing repeatedly can restore the original image. At the same time, three attacks are carried in the two shares, which contain content cropping, content exchange, and text addition. Some comparisons with other schemes present that the proposed scheme implements a better performance under some criteria. Theoretical analysis and experimental results demonstrate that the original image can be recovered losslessly even if two shares are tampered at the ration more than 50%.

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Band reordering heuristics for lossless satellite image compression with 3D-CALIC and CCSDS

Cited by 47 publications

References 21 publications

A secure lossless recovery for medical images based on image encoding and data self-embedding

A secure lossless recovery for medical images based on image encoding and data self-embedding

Comprehensive review of hyperspectral image compression algorithms

Medical images lossless recovery based on POB number system and image compression

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