Image Processing System using MATLAB-Based Analytics

TL;DR: The results largely present MATLAB as a veritable approach for image processing operations as well as providing an empirical-based method using two-dimensional discrete cosine transform (2D-DCT) derived from its coefficients.

Abstract: Owing to recent technological advancement, computers and other devices such as phones and digital cameras running several image editing software applications can be further exploited for other operations such as digital image processing operations. This paper attempts to conduct performance evaluation of the various image processing techniques using MATLAB-based analytics. Compared to the conventional techniques and other state-of-the-art applications used for image processing, MATLAB gives several advantages. MATLAB-based technique provides easy implementation and testing of algorithms without recompilation, and provides easy debugging with extensive data analysis and visualization. Besides, MATLAB's computational codes can be enhanced and exploited to process and create simulations of both still and video images. In addition, MATLAB codes are much concise compared to c++, thus making it easier for perusing and troubleshooting. MATLAB can handle errors prior to execution by proposing various ways to make the code faster.  The proposed technique enables advanced image processing operations such as image cropping/resizing, image denoising, blur removal, and image sharpening. The study aims at providing readers with the most recent image processing application-tools running on MATLAB platform. We also provide an empirical-based method of image processing using two-dimensional discrete cosine transform (2D-DCT) derived from its coefficients. With the different and most recent algorithms running on MATLAB toolbox, we provide simulations of several images to evaluate the performance of our proposed technique. The simulation results largely present MATLAB as a veritable approach for image processing operations.