Performance Augmentation of Cuckoo Search Optimization Technique Using Vector Quantization in Image Compression

For constructing the best local codebook for image compression, there are many Vector Quantization (VQ) procedures, but the simplest VQ procedure is the Linde-Buzo-Gray (LBG) procedure. Techniques such as the Gaussian Dissemination Function (GDF) are used for the searching process in generating a global codebook for particle swarm optimization (PSO), Honeybee mating optimization (HBMO), and Firefly (FA) procedures. However, when particle velocity is very high, FA encounters a problem when brighter fireflies are trivial, and PSO suffers uncertainty in merging. A novel procedure, Cuckoo Search-Kekre Fast Codebook Generation (CS-KFCG), is proposed that enhances Cuckoo Search-Linde-Buzo-Gray (CS-LBG) codebook by implementing a Flight Dissemination Function (FDF), which produces more speed than other states of the art algorithms with appropriate mutation expectations for the overall codebook. Also, CS-KFGC has generated a high Peak Signal Noise Ratio (PSNR) in terms of high duration (time) and better acceptability rate.

Automated summary

To construct the best local codebook for image compression, techniques such as Gaussian Dissemination Function (GDF) are commonly used in the searching process. However, existing algorithms like Firefly (FA) and Particle Swarm Optimization (PSO) face challenges in terms of brightness discrimination and merging uncertainty respectively. In this study, a novel procedure called Cuckoo Search-Kekre Fast Codebook Generation (CS-KFCG) is proposed, which enhances the codebook generation process by implementing a Flight Dissemination Function (FDF). CS-KFGC outperforms other state-of-the-art algorithms in terms of speed, mutation expectations, and achieved a high Peak Signal Noise Ratio (PSNR) with high duration and better acceptability rate.