Producing of High Quality Colored Images using Scalable Image Processing Techniques

Abstract

One of the many digital approaches that came from the image processing domain is picture enhancement. These approaches are employed to enhance the perceptibility of images, or to transform the image into a format more suitable for human or machine analysis, and to highlight intricate elements that might otherwise remain indistinct. The primary topic of this thesis is the utilization of the pseudo color approach, which is an image enhancement technique, to convert grayscale intensity images into color-coded images. An investigation into the various forms of pseudo color techniques that have been created in the past has been done in this work. Using the spectra returned by the Fourier transform of the input picture, the Pseudo color method applies three distinct digital filters—a high pass filter, a band pass filter, and a low pass filter—to achieve the desired effect: The Red, Green, and Blue components of the CRT electron cannons are then given the three filtered outputs that are generated, which are subsequently projected onto the screen. Therefore, a comprehensive package has been developed to execute the necessary procedures for generating the colored image. This bundle comprises two primary components. The initial one facilitates the execution of Fourier transformations and filtering operations. For the second part, a computed color table is used to mix the three components of Red, Green, and Blue to make and show the desired color. This means that each pixel in the original image will have a new value that matches the new color, which creates a new colored image. Also, Combining optimal partitioning with dynamic programming with a representation of the image for space-filling curve, we offer a novel algorithm for pseudo-coloring in this paper. The algorithm permits the fine-to-coarse assignment of triplet colors to the pixels of an image, thereby producing a pseudo-colored image that preserves either structure or detail. This is accomplished by initially considering the original gray levels in the image and then systematically decreasing them by optimal partitioning until reaching a specific number, which can include reducing the image to only two colors for a binary representation. The number of colors is output by the algorithm, and the specific allocation of colors is determined by the nature of the problem being addressed. Two sets of medical photos are used to illustrate how the algorithm is applied.