One of advanced form of compression is wavelet compression. JPEG 2000 is presented as an example of modern wavelet-based image compression. JPEG 2000 image compression standard makes use of DWT (Discrete Wavelet Transform). Image compression using wavelet transforms results in an improved compression ratio. DWT (Discrete Wavelet Transform) represents image as a sum of wavelet function (wavelets) on different resolution levels. So, the basis of wavelet transform can be composed of function that satisfies requirements of multiresolution analysis. The choice of wavelet function for image compression depends on the image application and the content of image. DWT can be used to reduce the image size without losing much of the resolutions computed. Thus it reduces the amount of memory required to represent given image. This paper presents a review of the fundamentals of image compression based on wavelet. This paper presents low bit rate video coding based on wavelet image compression. The superior performance of DWT is demonstrated with simulation results. In this study we have evaluated and compared three different wavelet families i.e. Daubechies, Coiflets, Biorthogonal. Image quality is measured using peak signal-to-noise ratio, compression ratio and also using visual image quality.

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Discrete wavelet transform (DWT) JPEG2000 subband encoding multiresolution low bit rate video coding peak signal-to-noise ratio compression ratio