Lossless image compression for storage reduction using pollination based optimization

Jindal, Priyanka; Kaur, Raj Bhupinder

doi:10.1109/cesys.2016.7889807

Cited by 3 publications

(1 citation statement)

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“…The overall results revealed that the CIFS method is found to be robust and attained significantly less MSE. Priyanka Jindal et al [30]introducedpollination based optimization (PBO) algorithm in image compression based on the fitness value of a DCT block of image data. By employing PBO algorithm, the local best and global best values of several DCT blocks are determined.…”

Section: Related Studiesmentioning

confidence: 99%

Modified Firefly Algorithm for Vector Quantization Codebook Design in Image Compression

Preethi,

Loganathan

2019

IJEAT

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In the recent days, the importance of image compression techniques is exponentially increased due to the generation of massive amount of data which needs to be stored or transmitted. Numerous approaches have been presented for effective image compression by the principle of representing images in its compact form through the avoidance of unnecessary pixels. Vector quantization (VA) is an effective method in image compression and the construction of quantization table is an important process is an important task. The compression performance and the quality of reconstructed data are based on the quantization table, which is actually a matrix of 64 integers. The quantization table selection is a complex combinatorial problem which can be resolved by the evolutionary algorithms (EA). Presently, EA became famous to resolve the real world problems in a reasonable amount of time. This chapter introduces Firefly (FF) with Teaching and learning based optimization (TLBO) algorithm termed as FF-TLBO algorithm for the selection of quantization table and introduces Firefly with Tumbling algorithm termed as FF-Tumbling algorithm for the selection of search space. As the FF algorithm faces a problem when brighter FFs are insignificant, the TLBO algorithm is integrated to it to resolve the problem and Tumbling efficiently train the algorithm to explore all direction in the solution space. This algorithm determines the best fit value for every bock as local best and best fitness value for the entire image is considered as global best. When these values are found by FF algorithm, compression process takes place by efficient image compression algorithm like Run Length Encoding and Huffman coding. The proposed FF-TLBO and FF-Tumbling algorithm is evaluated by comparing its results with existing FF algorithm using a same set of benchmark images in terms of Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Signal to Noise Ratio (SNR). The obtained results ensure the superior performance of FF-TLBO and FF-Tumbling algorithm over FF algorithm and make it highly useful for real time applications.

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Section: Related Studiesmentioning

confidence: 99%

Modified Firefly Algorithm for Vector Quantization Codebook Design in Image Compression

Preethi,

Loganathan

2019

IJEAT

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Quantization Table Selection Using Firefly with Teaching and Learning Based Optimization Algorithm for Image Compression

Preethi

Loganathan

2019

Handbook of Multimedia Information Security: Techniques and Applications

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A Review on Image Denoising using Bilateral Filtering

Goyal¹

2018

IJRASET

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Abstract:The bilateral filter is a non-linear technique that can denoise an image while respecting strong edges. Its ability to decompose an image into different scales without causing haloes after modification has made it ubiquitous in computational photography applications such as tone mapping, style transfer, relighting, and denoising. Even introduction in the field of 3D images new enhanced bilateral filter had been proposes. This content gives a graphical, natural introduction to bilateral filtering, a practical guide for efficient implementation and an overview of its various applications, and in addition mathematical analysis.

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Lossless image compression for storage reduction using pollination based optimization

Cited by 3 publications

References 0 publications

Modified Firefly Algorithm for Vector Quantization Codebook Design in Image Compression

Modified Firefly Algorithm for Vector Quantization Codebook Design in Image Compression

Quantization Table Selection Using Firefly with Teaching and Learning Based Optimization Algorithm for Image Compression

A Review on Image Denoising using Bilateral Filtering

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