Medical Image Enhancement Using an Adaptive Weight and Threshold Values
Seung‐Jong Kim · 한국인터넷방송통신학회 논문지 · 2012
Abstract By using an adaptive threshold and weight based on the wavelet transform and Haar transform, a novel image enhancement algorithm is proposed. First, a medical image was decomposed with wavelet transform and all high-frequency sub-images were decomposed with Haar transform. Secondly, noise in the frequency domain was reduced by the proposed soft-threshold method. Thirdly, high-frequency coefficients were enhanced by the proposed weight values in different sub-images. Then, the enhanced image was obtained through the inverse Haar transform and wavelet transform. But the pixel range of the enhanced image is narrower than a normal image. Lastly, the image’s histogram was stretched by nonlinear histogram equalization. Experiments showed that the proposed method can be not only enhance an image’s details but can also preserve its edge features effectively. Key Words : Wavelet and Haar Transform, Threshold, Weight, Nonlinear Histogram Equalization * 정회원, 한양여자대학교 컴퓨터정보과접수일자 : 2012년 9월 5일, 수정완료 : 2012년 10월 5일게재확정일자 : 2012년 10월 12일Received: 5 September 2012 / Revised: 5 October 2012 /Accepted: 12 October 2012