Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
Two-dimensional signal and image processing
Two-dimensional signal and image processing
Automatic moving object and background separation
Signal Processing - Video segmentation for content-based processing manipulation
MPEG Handbook
Three-dimensional wavelet transform video coding using symmetric codebook vector quantization
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
A new, fast, and efficient image codec based on set partitioning in hierarchical trees
IEEE Transactions on Circuits and Systems for Video Technology
Video segmentation for content-based coding
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
A robust scene-change detection method for video segmentation
IEEE Transactions on Circuits and Systems for Video Technology
Automatic segmentation of moving objects in video sequences: a region labeling approach
IEEE Transactions on Circuits and Systems for Video Technology
Object-based video coding by global-to-local motion segmentation
IEEE Transactions on Circuits and Systems for Video Technology
Optimal 3-D coefficient tree structure for 3-D wavelet video coding
IEEE Transactions on Circuits and Systems for Video Technology
Wavelet video coding with dependent optimization
IEEE Transactions on Circuits and Systems for Video Technology
Detection and compression of moving objects based on new panoramic image modeling
Image and Vision Computing
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The volume of patient monitoring video acquired in hospitals is very huge and hence there is a need for better compression of the same for effective storage and transmission. This paper presents a new motion segmentation technique, which improves the compression of patient monitoring video. The proposed motion segmentation technique makes use of a binary mask, which is obtained by thresholding the standard deviation values of the pixels along the temporal axis. Two compression methods, which make use of the proposed motion segmentation technique, are presented. The first method uses MPEG-4 coder and 9/7-biorthogonal wavelet for compressing the moving and stationary portions of the video respectively. The second method uses 5/3-biorthogonal wavelet for compressing both the moving and the stationary portions of the video. The performances of these compression algorithms are evaluated in terms of PSNR and bitrate. From the experimental results, it is found that the proposed motion technique improves the performance of the MPEG-4 coder. Among the two compression methods presented, the MPEG-4 based method performs better for bitrates less than 767 Kbps whereas for bitrates above 767 Kbps the performance of the wavelet based method is found superior.