{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,16]],"date-time":"2026-05-16T22:04:27Z","timestamp":1778969067884,"version":"3.51.4"},"reference-count":25,"publisher":"World Scientific Pub Co Pte Lt","issue":"01n02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Image Grap."],"published-print":{"date-parts":[[2014,1]]},"abstract":"<jats:p> Recorded medical images often represent a degraded version of the original scene due to imperfections in electronic or photographic medium used. The degradations may have many causes, but two dominant degradations are noise and blur. Restoration of blurred and noisy medical images is of fundamental importance in several medical imaging applications. Most of the medical image denoising techniques need removal of blur before the denoising. Denoising of medical images in presence of blur is a hard problem. Most of the wavelet transform-based denoising techniques use the orthonormal wavelets and suitable for image corrupted with only additive white Gaussian noise. In the present work, we have proposed a denoising algorithm for medical images based on the lifting-scheme and linear phase characteristic of biorthogonal wavelet transform. A level-dependent soft thresholding function has been used which is based on the standard deviation, the absolute mean and the absolute median of the wavelet coefficients. The linear phase characteristic of the biorthogonal filters used in denoising reduces the distortions at edge points of image. Also, the lifting schemes of the biorthogonal wavelet filters make the algorithm efficient and applicable in real time. Experimental results show that the proposed denoising method outperform standard wavelet, complex wavelet and curvelet-based denoising techniques in terms of the SNR and PSNR (in dB) and it offers effective noise removal from noisy medical images while maintaining sharpness of objects in the image. <\/jats:p>","DOI":"10.1142\/s0219467814500028","type":"journal-article","created":{"date-parts":[[2014,6,6]],"date-time":"2014-06-06T06:07:01Z","timestamp":1402034821000},"page":"1450002","source":"Crossref","is-referenced-by-count":8,"title":["Medical Image Denoising Based on Soft Thresholding Using Biorthogonal Multiscale Wavelet Transform"],"prefix":"10.1142","volume":"14","author":[{"given":"Om","family":"Prakash","sequence":"first","affiliation":[{"name":"Department of Electronics and Communication, University of Allahabad, Allahabad 211002, India"},{"name":"Centre of Computer Education, Institute of Professional Studies, University of Allahabad, Allahabad 211002, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ashish","family":"Khare","sequence":"additional","affiliation":[{"name":"Department of Electronics and Communication, University of Allahabad, Allahabad 211002, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2014,6,5]]},"reference":[{"key":"rf2","volume-title":"Digital Image Processing","author":"Gonzalez R. 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