Medical X-Ray Image Enhancement Based on Wavelet Domain Homomorphic Filtering and CLAHE

For the medical X-ray image with low brightness, low contrast and noise, we proposed an image enhancement algorithm which based on wavelet domain homomorphic filtering and contrast limited adaptive histogram equalization (CLAHE). Firstly, the image is decomposed by wavelet transformation, the image is decomposed into low-frequency and high-frequency coefficients of 1st layer of wavelet domain. Then the low frequency coefficients are processed by an improved homomorphic filter, and then linear amplified. The high frequency coefficients are processed by wavelet threshold shrinkage, and then the wavelet reconstruction is performed. Finally, the contrast limited adaptive histogram equalization (CLAHE) is used to modify the image's histogram, and the processing of the image is completed. The quality of image enhancement is carried on the subjective and objective evaluation, and compared with some other enhancement algorithms. Experimental results show that the algorithm can effectively enhance the texture detail of medical X-ray images, increasing the brightness and contrast, suppress noise, better than the general traditional enhancement algorithms.