ABSTRACT
A joint time–frequency localized three-band biorthogonal wavelet filter bank to compress Electrocardiogram signals is proposed in this work. Further, the use of adaptive thresholding and modified run-length encoding resulted in maximum data volume reduction while guaranteeing reconstructing quality. Using signal-to-noise ratio, compression ratio (C(R)), maximum absolute error (E(MA)), quality score (Q(s)), root mean square error, compression time (C(T)) and percentage root mean square difference the validity of the proposed approach is studied. The experimental results deduced that the performance of the proposed approach is better when compared to the two-band wavelet filter bank. The proposed compression method enables loss-less data transmission of medical signals to remote locations for therapeutic usage.
Subject(s)
Electrocardiography , Joints , Methods , Signal-To-Noise RatioABSTRACT
Objective: An automatic seamless stitching method with spinal X-ray image sequence is presented in this paper. Methods: First, biorthogonal wavelet transform is used to implement decomposing of the multi-resolution and the effective edge of the image can be extracted by this method combined with Canny operator. The feature points of the image can be obtained by calculating the edge contour matrix E and the value matrix H. Second, the roughly matching of feature points can be achieved by using Normalized Cross Correlation (NCC) algorithm and the random sample consensus (RANSAC) algorithm is introduced to remove false matching pairs and to achieve precisely matching. Third, the image sequence is automatically sorted with the improved genetic algorithm to achieve automatic stitching. At last, the weighted average fusion algorithm is appfied to achieve smooth and seamless image stitching. This algorithm is robust for the weak-contrast X-ray image sequence. Results: Experimental results show that high-quality and fast image sequence stitching can be obtained automatically by using this method. Conclusions: To a certain extent, it overcomes the shortcomings of X-ray image sequence such as the strong image noise, concentration of values ofpixels, blurred boundaries, large overlap area and the sequence constraint, and therefore it may be applied to in medical imaging field widely.