A Hybrid Bat‐Genetic Algorithm–Based Novel Optimal Wavelet Filter for Compression of Image Data
Renjith V. Ravi, Kamalraj Subramaniam · 2021
In the past two decades, significant advances have been made in the fields of image cryptography and compression, motivated by a growing demand for visual information storage and transmission. However, including both compression and encryption in a single algorithm can be significant research which can reduce the computation overhead and also improve the security in transmission. In this paper, a novel optimal wavelet filter bank based on hybrid bat-genetic algorithm for image compression is proposed. Initially, a novel optimization algorithm based on hybridizing the techniques of bat algorithm and genetic algorithm is developed, and further, an optimal wavelet filter bank is derived from the hybrid bat-genetic optimization algorithm. This filter bank is then used for wavelet-based image compression of images taken from unmanned vehicle, and then, the compressed image is encrypted using chaos theory–based encryption. The strategy involves three modules, namely, optimized transformation module, compression and encryption module, and receiver module. Initially, the input image is sub-band coded using hybrid bat-genetic algorithm– based optimized DWT. Subsequently, the encoding using SPIHT and chaos-based encryption is carried out. In receiver module, the received signal from the AWGN channel is demodulated, decrypted, and decompressed to have the estimated image. From the results, we can infer that the use of proposed filter and the technique has produced better image quality when compared to existing techniques.