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Detecting and tracking human in still or video images provides a promising technology development and solution to many real world problems. Moreover, detecting human may be the first step to put forward the next logical steps for many applications. But, it is a challenging task due pose, dresses, color and occlusion. This paper proposes a study of human detection in static images in different view. In the literature, numerous works had been proposed to detect a single human in an image. So, the survey has been conducted for detection of multiple humans without occlusion, detection of multiple human with occlusion and human detection in fused image. Due to the difficulties found during the process of human detection such as occlusion and shadow, people in group, main focus has been given to multiple-human detection. [ABSTRACT FROM AUTHOR]

This paper aims at providing an image enhancement algorithm for digital images especially corrupted by various noises. Image restoration is a technique used to construct a composite image containing mutual and significant information from noisy source image. The novelty of this paper is implemented via applying contourlet transform as well as directional filter bank. The source image is decomposed into base and detail layers, firstly. Then, the detail layer is further decomposed by DFT filter banks to pass away noises. The denoisy detail layer is appended to the base layer of the corresponding source image to obtain noise-free source images. Finally, all the noise-free source images are fused using average fusion rule. Resulted images using our algorithm are compared with state of the art denoisy methods to show the effectiveness of the proposed method. Our proposed method outperforms the state of the art fusion method. [ABSTRACT FROM AUTHOR]