A comparative analysis of image compression by different wavelets techniques using matlab Verma Shalini, Mishra Pawan Kumar Department of Computer Science and Engineering, Faculty of Technology, Uttarakhand Technical University, Dehradun, India Online published on 8 May, 2017. Abstract An image generally needs considerable storage and resources, so image compression is an effective technique to overcome these requirements. This paper includes different wavelet techniques used for data compression or image compression. Image Compression generally followed in computer graphics such as in Internet, digital library, mobile and multimedia. The volume of information stored in an image or video can be compressed by using Image compression techniques. There are many image compression techniques available such as JPEG, DCT (Discrete Cosine Transform), DWT (Discrete Wavelet Transform), Wavelet, Huffman Coding, Quantization, Lossy Compression or Lossless Compression. The main objective of this paper is to select the appropriate method of wavelet towards compression of the image. Also the quality of the reconstructed image has been estimated in terms of image quality metrics such as PSNR (Peak Signal-to-Noise ratio) and CR (compression ratio). In this paper, the various wavelets methods such as Haar, Daubechies, and Biorthogonal, Coiflets and Symlet wavelet are applied to an image and then their qualitative and quantitative analysis results are compared in terms of PSNR values, MSE and compression ratios. Top Keywords Image Compression, Wavelet techniques, CR (compressiond ratio), PSNR (Peak Signalto-Noise ratio), MSE (Mean Square Error), DCT, DWT. Top |