Image Compression Using Multithresholding Technique to Enhance Huffman Technique
Prabhjot Kaur, Sarbdeep Singh · 2012
Image compression means reducing the size of graphics file, text, without degrading its quality. Two techniques are exist for compression to find out, whether the reconstructed image has to be exactly same as the original or some unidentified loss or changes may be incurred. First is lossy technique (in this some of data may be lost). Second is lossless technique (in this technique the reconstructed image is exactly same as the original) Image compression is an essential technology in multimedia and digital communication f ields. Ideally, an image compression technique removes redundancy, and efficiently encodes what remains .The Process to remove the redundancy is called compression. Most of the existing image coding algorithm is based on the correlation between adjacent pixels and therefore the compression ratio is not high. Fractal coding is a potential image compression method, which is based on the ground breaking work of Barnsley and was developed to a usable state by Jacquin. The fractal-based schemes exploit the self-similarities that are inherent in many real world images for the purpose of encoding an image as a collection of transformations. Here in this hybrid model we are going to propose a Nobel technique which is the combination of multithresholding technique and huffman techniques. This paper presents Huffman compression technique which is lossless technique. To enhance the huffman technique we are using multithresholding technique which is lossy technique. We implement lossless technique so our PSNR and MSE will be better than the old algorithms and due to multithresholding we will get good level of compression.