Digital Imaging Procesing Techiques

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Image Processing Image processing is any form of signal processing for which the input is an image, such as a photograph or video frame, the output of the image processing may be either an image or a set of characteristics or parameters related to the image. Most image processing techniques involve treating the image as a two-dimensional signal and applying standard signal processing techniques to it. Image processing usually refers to digital image processing, but optical and analog image processing also are possible. The acquisition of images (producing the input image in the first place) is referred to as imaging. Image processing refers to processing of a 20 picture by a computer. An image is defined in the “real world” is considered to be a function of two real variables, for example, a (x, y) with a as the amplitude (eg. Brightness) of the image at the real coordinate position (x, y). Most usually, image processing systems require that the image be available in digitized form, that is ,arrays of finite length binary words for Digestion, the given image is sampled on a discrete grid and each sample or pixel is quantized using finite number of bits. The digitized image is processed by a computer. To display a digital image, it is first converted into analog signal which is scanned onto a display. Before going to processing an image, it is converted into digital form. Digitization includes sampling of image and quantization of sampled values. After converting the image into bit information, processing is performed. This processing technique may be image enhancement, image restoration, and image compression. Image enhancement: It refers to accentuation, or sharpening, of image features such as boundaries, or contrast to... ... middle of paper ... ...-level processes on images involve tasks such as segmentation (partitioning an image into regions or objects), descrip¬tion of those objects to reduce them to a form suitable for computer process¬ing, and classification (recognition) of individual objects. A mid-level process is characterized by the fact that its inputs generally are images, but its out¬puts are attributes extracted from those images (e.g., edges, contours, and the identity of individual objects). Finally, high-level processing involves “making sense” of an ensemble of recognized objects, as in image analysis, and, at the far end of the continuum, performing the cognitive functions normally associated with human vision. In particular, digital image processing is the only practical technology for: • Classification • Feature extraction • Pattern recognition • Projection • Multi-scale signal analysis

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