Abstract:

BACKGROUND: As a routine way of checking, X-ray examination has been widely used, but because of the limitations of existing technology, X-ray images have disadvantages of low intensity contrast, and noise. Therefore, nowadays the X-ray images are often not meet medical requirements.
OBJECTIVE: To enhance and denoise X-ray images with low intensity contrast and noise, to achieve the purpose of medical understanding and recognition.
METHODS: Due to the shortage of image enhancement algorithm in the spatial domain and transform domain, an algorithm based on gray-contrast and adaptive wavelet transform was addressed. First, gray-scale ranges needed to strengthen or weaken were selected. The algorithm of eight neighborhood gray-scale contrast enhancement was used to enhance the X-ray image, and algorithm of median filtering was used to smooth the image. Second, the X-ray image was decomposed using wavelet decomposition algorithm, and the size of the correlation coefficients between adjacent layers were used to determine the details and noise of the image.
RESULTS AND CONCLUSION: The algorithm based on gray-contrast and adaptive wavelet transform integrates methods based on space domain enhancement or transform domain, which is better than enhancement method alone. The results show that this method achieved a good enhancement and denoising effect. Compared with the results of only contrast and modified the wavelet coefficients, this method obtains a better enhancement and denoising effect.