The Image Compression Technology Based On Lifting Algorithm Of Wavelet Transformation

Many application domains need store and transmit a great deal of digital images with the rapid development of computer, network, communication and multimedia technology. So it is required imminently that effective measure be adopted to deal with the images. The concise Fourier transformation——DCT(discrete cosine transformation) is a common tool to compress image and video. Nevertheless with in-depth development and application, disadvantages of blocked DCT transformation coding unveil incessantly especially reconstructed images have diamond effect and fly mosquito noise. Compared with DCT, wavelet transformation has fine time and frequency localized characteristics, multi-resolution analysis and direction selectivity matching with human vision system (HVS), and wavelet transformation is processed on the whole image avoiding the diamonds effect of DCT. The new image compression criterion——JPEG 2000 applying wavelet transformation technology achieves good compression effect.Traditional wavelet transformation is calculated by convolution operation that needs a great lot of calculation and room. Wavelet lifting algorithm as generation-2 wavelet turns into main method of DWT featuring fast algorithm, operation simpleness, integer lifting etc. Through analyzing and discussing wavelet transformation theory, three different compression methods for grey, colorful and video image are designed. The main process that the image is compressed is : one, lead into the image data, convert the colorful image data of the format of RGB into the data of the format of YUV ; two, make use of the wavelet lifting transformation to carry on the resolving operation to the image data ; three, the wavelet coefficients resolved, are quantized with different quantizing mode for gray or colorful image ; four, carry on coding ; finally , coding stream is yielded.Making use of the different static image and video image to carry on the experiment with the above algorithms respectively, obtain the good compression result. The wavelet transformation programs according to lifting algorithm reach the level of commercial software. Under the same condition, the calculation time is reduced obviously . The compression efficiency is improved comparing with the traditional wavelet algorithm. The quality of image restituted is good. This algorithm has low cost, will be widely used with continuous improvement.