A Review on Various Techniques to Overcome Constraints during Image Acquisition

The elimination of blur due to camera shake and motion of the scene is been considered as a research topic in Image processing. An algorithm can be used to reduce the blur, which is capable of grouping many images, in that images less blurred image from each frame can be preferred through a weighted average in the Fourier Transform. The algorithm is simple to implement and very easy to define theoretically. To reduce the computation, complexity and to improve the quality of the image various algorithm has been proposed, which ultimately focuses on removal of blur. Irregular illumination can introduce severe distortions in the resulting images, decreasing the visibility of anatomical structures and consequently demoting the performance of the automated segmentation of these structures. There are several operators for example Prewitt, Sobel, Roberts, Canny edge detector are available, in which a mask is used as a template, that can be used to detect the edge pixels. There are Various methods and algorithms such as CNN, Morphological operations that are used to overcome this blur removal problem. As a result, it can be reduced and detected for several image issues. Among the operators Canny edge detector serves to be the best and for Blur correction Morphological operations has proven to be the classic one.