Feature enhancement angiographic images in medical diagnosis

This paper suggest three new proposed algorithms for the feature enhancement in the angiographic images. The first approach is based on mixing the features of Homomorphic Way and the Additive Wavelet Transform (AWT) with Six Sub Bands (AWHS). The idea behind this model is based on decomposing the image into sub-bands in an additive fashion using the AWT. The homomorphic processing is applied on each sub band, separately. The second approach suggests modification for histogram equalization (MHE) for enhancement angiographic images. The MHE is depended on applying the Histogram Equalization (HE) on angiographic images and suggest modification for clip limit for the HE. Third suggested approach merges the benefits of the Histogram Processing with the features of Undecimated AWT (HPUAT) and homomorphic method. The main idea of this model depends on applying The MHE on the angiographic image. Then, the resultant image is decomposed into sub-bands using the AWT. The homomorphic enhancement is implemented on each sub-band, separately, up to the sixth sub-band. This method is performed on the angiographic image in the log domain by decomposing the image into illumination and reflectance components. The illumination is attenuated, while the reflectance is magnified. Applying this model on each sub-band obtains more details in the angiographic image. The performance evaluations are entropy, average gradient, contrast improvement factor and Sobel edge magnitude point of views. Simulation results show that the third proposed approach gives superior image quality for angiographic images.