Abstract
In this paper the image compression problem is analyzed using genetic clustering algorithms based on the pixels of the image. The main problem to solve is to find an algorithm that performs the clustering efficiently. The possibility of solving clustering problems with genetic algorithms provides optimal solution. The present work makes use of genetic clustering algorithms to obtain an ordered representation of the image and then applies the DWT (Discrete Wavelet Transformation) to compress the image. The image quality is measured using PSNR measure. The genetic algorithm (GA)-based compression image has more PSNR value compared to the image without GA. It shows that the quality of the image is good for GA based compression. Also it reduces the problem of memory utilization efficiently due to compression and at the same time quality of the image is maintained due to GA. Keywords: Genetic algorithms, clustering, image compression, discrete wavelet transformation.
Highlights
Klein and Dubes (1989) have applied performs the clustering efficiently
The execution of Genetic Algorithm (GA) is relatively genetic algorithm (GA)-based compression image controllable and flexible to cater for a specific has more Peak signal –to- noise ratio (PSNR) value compared to the image application (Brown et al, 1989)
The technique of clustering with genetic algorithm was applied to image compression
Summary
The technique of clustering with genetic algorithm was applied to image compression. Basic operators of selection, crossing over and mutation were utilized. The main idea is to divide the problem into parts and to apply the clustering technique to each part independently and this produces optimal representation for transformation. The results show that the GA outperforms the DWT in terms of both PSNR and visual quality. Further research along this line is the integration of Genetic Algorithm quantization with other transform such as DCT. The quantization of these signal coefficients, if successful, will yield high compression and high
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call