A novel saliency based image compression algorithm using low complexity block truncation coding

Nayak, D.; Ray, Kanan Bala; Kar, T.; Kwan, Chiman

doi:10.1007/s11042-023-15694-2

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Cited by 3 publications

References 37 publications

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An enhanced AMBTC for color image compression using color palette

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Zhang,

Yang

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An enhanced AMBTC for color image compression using color palette

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Zhang,

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Multimed Tools Appl

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High-quality Image Compression Algorithm Design Based on Unsupervised Learning

Han,

Mo,

Zhao

et al. 2024

Preprint

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Increasingly massive image data is restricted by conditions such as information transmission and reconstruction, and it is increasingly difficult to meet the requirements of speed and integrity in the information age. To solve the urgent problems faced by massive image data in information transmission, this paper proposes a high-quality image compression algorithm based on unsupervised learning. Among them, a content-weighted autoencoder network is proposed to achieve image compression coding on the basis of a smaller bit rate to solve the entropy rate optimization problem. Binary quantizer are used for coding quantization, and importance map are used to achieve better bit allocation. The compression rate is further controlled and optimized. A multi-scale discriminator suitable for the generative adversarial network image compression framework is designed to solve the problem that the generated compressed image is prone to blurring and distortion. Finally, through training with different weights, the distortion of each scale is minimized, so that the image compression can achieve a higher quality compression and reconstruction effect. The experimental results show that the algorithm model can save the details of the image and greatly compress the memory of the image. Its advantage is that it can expand and compress a large number of images quickly and efficiently, and realize the efficient processing of image compression.

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A Performance Study of Different Approaches of Digital Image Compression Techniques

Mansouri,

Hamda Othman,

Asklany

et al. 2024

Eng. Technol. Appl. Sci. Res.

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Today, managing a large amount of information becomes increasingly crucial. Efficient storage and retrieval of digital data are essential for their effective utilization. This study investigates the efficacy of Spatial Domain Image Compression Techniques, which directly manipulate the original image to reduce its size by leveraging pixel spatial relationships. These techniques segment the image into blocks and process each block independently. Evaluation entails measuring perceptual quality through metrics, such as PSNR, WPSNR, NMSE, and SSIM applied to the compressed image. Experimental results provide a comparative analysis of the performance of these techniques.

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A novel saliency based image compression algorithm using low complexity block truncation coding

Cited by 3 publications

References 37 publications

An enhanced AMBTC for color image compression using color palette

An enhanced AMBTC for color image compression using color palette

High-quality Image Compression Algorithm Design Based on Unsupervised Learning

A Performance Study of Different Approaches of Digital Image Compression Techniques

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