Efficient Performance Analysis of Image Enhancement Filtering Methods Using MATLAB
K Nagaiah
Dr. K Nagaiah, FST, ECE, THE ICFAI University Raipur, Raipur, CG-India.
Manuscript received on 09 December 2023 | Revised Manuscript received on 18 December 2023 | Manuscript Accepted on 15 January 2024 | Manuscript published on 30 January 2024 | PP: 1-5 | Volume-13 Issue-2, January 2024 | Retrieval Number: 100.1/ijitee.B977713020124 | DOI: 10.35940/ijitee.B9777.13020124
Open Access | Editorial and Publishing Policies | Cite | Zenodo | OJS | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Image enhancement is both an art and a science, playing a pivotal role in enhancing the quality of high-resolution images like those captured by digital cameras. Its primary goal is to unveil hidden details within an image and augment the contrast in images with low contrast. This method provides a range of options for enhancing the visual appeal of images, making it a vital tool in various applications that encounter challenges such as noise reduction, degradation, and blurring. In this paper, we implemented frequency-domain low-pass filters, including the ideal low-pass filter, the Butterworth low-pass filter, and the Gaussian low-pass filter, with execution time analysis using MATLAB. The Butterworth low-pass filter gave better results than the other two with less execution time.
Keywords: MSE, PSNR, Image Enhancement, Frequency Domain, Low Pass Filters, Image Processing, Execution Time.
Scope of the Article: Low-power design