Transmitting digital images via mobile device is often subject to bandwidth which are incompatible with high data rates. embeddedcoding for progressive image transmission has recently gained popularity in image compr...
详细信息
ISBN:
(纸本)0819461148
Transmitting digital images via mobile device is often subject to bandwidth which are incompatible with high data rates. embeddedcoding for progressive image transmission has recently gained popularity in image compression community. However, current progressive wavelet-based image coders tend to send information on the lowest-frequency wavelet coefficients first. At very low bit rates, images compressed are therefore dominated by low frequency information, where high frequency components belonging to edges are lost leading to blurring the signal features. This paper presents a new image coder employing edge preservation based on local variance analysis to improve the visual appearance and recognizability of compressed images. The analysis and compression is performed by dividing an image into blocks. Fast lifting wavelet transform is developed with the advantages of being computationally efficient and boundary effects minimized by changing wavelet shape for handling filtering near the boundaries. A modified SPIHT algorithm with more bits used to encode the wavelet coefficients and transmitting fewer bits in the sorting pass for performance improvement, is implemented to reduce the correlation of the coefficients at scalable bit rates. Local variance estimation and edge strength measurement can effectively determine the best bit allocation for each block to preserve the local features by assigning more bits for blocks containing more edges with higher variance and edge strength. Experimental results demonstrate that the method performs well both visually and in terms of MSE and PSNR. The proposed image coder provides a potential solution with parallel computation and less memory requirements for mobile applications.
embeddedcoding for progressive image transmission has recently gained popularity in image compression community. However, current progressive wavelet-based image coders tend to be complex and computationally intense ...
详细信息
ISBN:
(纸本)9728865643
embeddedcoding for progressive image transmission has recently gained popularity in image compression community. However, current progressive wavelet-based image coders tend to be complex and computationally intense requiring large memory space. The encoding process usually sends information on the lowest-frequency wavelet coefficients first. At very low bit rates, images compressed are therefore dominated by low frequency information, where high frequency components belonging to edges are lost leading to blurring the signal features. This paper presents a new image coder for real-time transmission, employing edge preservation based on local variance analysis to improve the visual appearance and recognizability of compressed images. The analysis and compression is performed by dividing an image into blocks. Lifting wavelet filter bank is constructed for image decomposition and reconstruction with the advantages of being computationally efficient and boundary effects minimized. A modified SPIHT algorithm with more bits used to encode the wavelet coefficients and transmitting fewer bits in the sorting pass for performance improvement, is used to reduce the correlation of the coefficients at scalable bit rates. Local variance estimation and edge strength measurement can effectively determine the best bit allocation for each block to preserve the local features. Experimental results demonstrate that the method performs well both visually and in terms of quantitative performance measures, and offers error resilience feature that is evaluated using a simulated transmission channel with random error.
暂无评论