Perceptually Lossless Image Compression with Error Recovery

Kwan, Chiman; Shang, Eric L.; Tran, Trac D.

doi:10.1145/3271553.3271602

Cited by 8 publications

(7 citation statements)

References 4 publications

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“…One image example shown in Figure 5 demonstrates that HVS and HVS-M have high correlation with human subjective evaluation results. In the past, we have used HVS and HVS-m in several applications [30] [31].…”

Section: Performance Metricsmentioning

confidence: 99%

Perceptually Lossless Compression for Mastcam Multispectral Images: A Comparative Study

Kwan¹,

Larkin²

2019

JSIP

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The two mast cameras, Mastcams, onboard Mars rover Curiosity are multispectral imagers with nine bands in each. Currently, the images are compressed losslessly using JPEG, which can achieve only two to three times of compression. We present a comparative study of four approaches to compressing multispectral Mastcam images. The first approach is to divide the nine bands into three groups with each group having three bands. Since the multispectral bands have strong correlation, we treat the three groups of images as video frames. We call this approach the Video approach. The second approach is to compress each group separately and we call it the split band (SB) approach. The third one is to apply a two-step approach in which the first step uses principal component analysis (PCA) to compress a nine-band image cube to six bands and a second step compresses the six PCA bands using conventional codecs. The fourth one is to apply PCA only. In addition, we also present subjective and objective assessment results for compressing RGB images because RGB images have been used for stereo and disparity map generation. Five well-known compression codecs, including JPEG, JPEG-2000 (J2K), X264, X265, and Daala in the literature, have been applied and compared in each approach. The performance of different algorithms was assessed using four well-known performance metrics. Two are conventional and another two are known to have good correlation with human perception. Extensive experiments using actual Mastcam images have been performed to demonstrate the various approaches. We observed that perceptually lossless compression can be achieved at 10:1 compression ratio. In particular, the performance gain of the SB approach with Daala is at least 5 dBs in terms peak signal-to-noise ratio (PSNR) at 10:1 compression ratio over that of JPEG. Subjective comparisons also corroborated with the objective metrics in that perceptually lossless compression can be achieved even at 20 to 1 compression.

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Section: Performance Metricsmentioning

confidence: 99%

Perceptually Lossless Compression for Mastcam Multispectral Images: A Comparative Study

Kwan¹,

Larkin²

2019

JSIP

Self Cite

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“…Filtered image g(x, y) has been feed to the input of the wavelet transform. Discrete wavelet transform down sampled the image g(x, y) into two different sub bands image such as low frequency band image and high frequency band image [23][24]. Again the low frequency sub band has been down sampled.…”

Section: Discrete Wavelet Transformmentioning

confidence: 99%

Image Preservation using Wavelet Based On Kronecker Mask, Birge - Massart And Parity Strategy

Chithra¹,

Tamilmathi²

2019

IJITEE

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Image carries more information about the ideas than text. Growth of social media, images has become the universal language because it is more interactive. Images are used in different fields like medical, multimedia, industries etc. When using the images, we need to find effective storage and transmission methods to reduce storage size and transmission time. Lossless and lossy are two ways to compress the image to reduce the storage and transmission time. The proposed method implements the concept of lossless image compression using the method of Kronecker delta notation, wavelet based on Birge-Massart strategy and parity strategy. This paper presents that enhancing the image by applying the Kronecker delta notation as the mask and applying the wavelet based on Birge-Massart strategy, finally applying the parity threshold to compress the image. The proposed method is compared the compression ratio (CR) with the existing lossless compression methods such as Birge – Massart without the enhanced method and Unimodal method. This proposed algorithm is very simple and more efficient to reduce the storage capacity and maintain the quality of an image than the existing lossless compression techniques. The experimental result shows that the Birge-Massart strategy combined with Kronecker mask and parity threshold produces the best CR than the simple Birge- Massart(without enhancement and threshold) strategy. This efficient method is proved by without loss of information of an original image with low MSE, high PSNR and high CR. An experimental result shows that the proposed algorithm achieved maximum CR of 146% on medical images and maximum CR of 19.2% on standard images than the existing methods.

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“…It should be noted that this paper is an extension of our conference paper [19]. There are several key differences.…”

Section: Introductionmentioning

confidence: 97%

“…There are several key differences. First, we corrected an issue related to the compression ratio computation in our earlier study [19]. Since the input image formats for different codecs are different, we converted all the raw images to different image formats in our earlier study.…”

Section: Introductionmentioning

confidence: 99%

“…However, one issue is that the converted file sizes are slightly different for different formats. In our earlier study [19], each codec was using its own set for computing the compression ratios, causing some slight differences in terms of compression ratios. In this study, we consistently used the original image sizes as references instead of the converted ones.…”

Section: Introductionmentioning

confidence: 99%

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A Comparison of Compression Codecs for Maritime and Sonar Images in Bandwidth Constrained Applications

et al. 2019

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Since lossless compression can only achieve two to four times data compression, it may not be efficient to deploy lossless compression in bandwidth constrained applications. Instead, it would be more economical to adopt perceptually lossless compression, which can attain ten times or more compression without loss of important information. Consequently, one can transmit more images over bandwidth limited channels. In this research, we first aimed to compare and select the best compression algorithm in the literature to achieve a compression ratio of 0.1 and 40 dBs or more in terms of a performance metric known as human visual system model (HVSm) for maritime and sonar images. Our second objective was to demonstrate error concealment algorithms that can handle corrupted pixels due to transmission errors in interference-prone communication channels. Using four state-of-the-art codecs, we demonstrated that perceptually lossless compression can be achieved for realistic maritime and sonar images. At the same time, we also selected the best codec for this purpose using four performance metrics. Finally, error concealment was demonstrated to be useful in recovering lost pixels due to transmission errors.

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Perceptually Lossless Image Compression with Error Recovery

Cited by 8 publications

References 4 publications

Perceptually Lossless Compression for Mastcam Multispectral Images: A Comparative Study

Perceptually Lossless Compression for Mastcam Multispectral Images: A Comparative Study

Image Preservation using Wavelet Based On Kronecker Mask, Birge - Massart And Parity Strategy

A Comparison of Compression Codecs for Maritime and Sonar Images in Bandwidth Constrained Applications

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