Medical Image Enhancement Using Pixel Operation

 We define a digital image as a two-dimensional array of numbers that represent the real, continuous  intensity distribution of a spatial signal. The continuous spatial signal is sampled at regular intervals, and the intensity is quantized to a finite number of levels.

            Each element of the array is referred to as a picture element or pixel. The digital image is defined as a spatially distributed intensity signal f (m, n), where f is the intensity of the pixel, and m and n define the position of the pixel along a pair of orthogonal axes usually defined as horizontal and vertical. We shall assume that the image has M rows and N columns and that the digital image has P quantized levels of intensity (gray levels) with values ranging from 0 to P − 1. The histogram of an image, commonly used in image enhancement and image characterization, is defined as a vector that contains the count of the number of pixels in the image at each gray level.

 PIXEL OPERATIONS:

   This methods of image enhancement is depend only on the pixel gray level and do not take into account the pixel neighborhood or whole-image characteristics

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Compensation for Nonlinear Characteristics of Display or Print Media:

           

            Digital images are generally displayed on cathode ray tube (CRT) type display systems or printed using some type of photographic emulsion. Most display mechanisms have nonlinear intensity characteristics that result in a nonlinear intensity profile of the image when it is observed on the display.

B. Intensity Scaling:

           

            Intensity scaling is a method of image enhancement that can be used when the dynamic range of the acquired image data significantly exceeds the characteristics of the display system, or vice versa. It may also be the case that image information is present in specific narrow intensity bands that may be of special interest to the observer. Intensity scaling allows the observer to focus on specific intensity bands in the image by modifying the image such that the intensity band of interest spans the dynamic range.

C. Histogram Equalization:

            Define although intensity scaling can be very effective in enhancing image information present in specific intensity bands, often information is not available a priori to identify the useful intensity bands. In such cases, it may be more useful to maximize the information conveyed from the image to the user by distributing the intensity information in the image as uniformly