Wavelet-Based Image Compression and its Application (International Journal of Engineering and Computer Science, 2017)
Image compression addresses the problem of reducing the amount of data required to represent a digital image. The objective of this paper is to evaluate set of wavelet for image compression. Image compression using wavelet transforms result in an improved compression ratio. Wavelet transformation is the technique that provides both spatial and frequency domain information. These properties of wavelet transform greatly help in identification and selection of significant and non –significant coefficients amongst the wavelet coefficients. DWT (Discrete Wavelet Transform) represent image as a sum of wavelet function (Wavelet) on different resolution levels. So, the basis of wavelet transform can be composed of function that satisfies requirement of multi resolution analysis. The choice of wavelet function for image compression depends on the image application and content of image. A review of the fundamental of image discussed important features of wavelet transform in compression of images. It also reduces the amount of time required for image to be sent over Internet or download from web page. After this process, whenever the original image is required, then the compressed image is decompressed to construct the original image or an approximation of it.