Search Word(s) in Title, Keywords, Authors, and Abstract: Image Enhancement

X-Ray Image Enhancement Using a Boundary Division Wiener Filter and Wavelet-Based Image Fusion Approach
Sajid Ullah Khan, Wang Yin Chai, Chai Soo See and Amjad Khan
Page: 35~45, Vol. 12, No.1, 2016
10.3745/JIPS.02.0029

Keywords: Image Enhancement, Image Fusion, Poisson/Impulse Noise, Sharpening, Wavelet Transform
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To resolve the problems of Poisson/impulse noise, blurriness, and sharpness in degraded X-ray images, a novel and efficient enhancement algorithm based on X-ray image fusion using a discrete wavelet transform is proposed in this paper. The proposed algorithm consists of two basics. First, it applies the techniques of boundary division to detect Poisson and impulse noise corrupted pixels and then uses the Wiener filter approach to restore those corrupted pixels. Second, it applies the sharpening technique to the same degraded X-ray image. Thus, it has two source X-ray images, which individually preserve the enhancement effects. The details and approximations of these sources X-ray images are fused via different fusion rules in the wavelet domain. The results of the experiment show that the proposed algorithm successfully combines the merits of the Wiener filter and sharpening and achieves a significant proficiency in the enhancement of degraded X-ray images exhibiting Poisson noise, blurriness, and edge details.


A Robust Face Detection Method Based on Skin Color and Edges
Deepak Ghimire and Joonwhoan Lee
Page: 141~156, Vol. 9, No.1, 2013
10.3745/JIPS.2013.9.1.141
Keywords: Face Detection, Image Enhancement, Skin Tone Percentage Index, Canny Edge, Facial Features
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In this paper we propose a method to detect human faces in color images. Many existing systems use a window-based classifier that scans the entire image for the presence of the human face and such systems suffers from scale variation, pose variation, illumination changes, etc. Here, we propose a lighting insensitive face detection method based upon the edge and skin tone information of the input color image. First, image enhancement is performed, especially if the image is acquired from an unconstrained illumination condition. Next, skin segmentation in YCbCr and RGB space is conducted. The result of skin segmentation is refined using the skin tone percentage index method. The edges of the input image are combined with the skin tone image to separate all non- face regions from candidate faces. Candidate verification using primitive shape features of the face is applied to decide which of the candidate regions corresponds to a face. The advantage of the proposed method is that it can detect faces that are of different sizes, in different poses, and that are making different expressions under unconstrained illumination conditions