Gurwinder Kaur*, Ashwani Kumar
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 281-296, 2023, DOI:10.32604/iasc.2023.026393
Abstract Blur is produced in a digital image due to low pass filtering, moving objects or defocus of the camera lens during capture. Image viewers are annoyed by blur artefact and the image's perceived quality suffers as a result. The high-quality input is relevant to communication service providers and imaging product makers because it may help them improve their processes. Human-based blur assessment is time-consuming, expensive and must adhere to subjective evaluation standards. This paper presents a revolutionary no-reference blur assessment algorithm based on re-blurring blurred images using a special mask developed with a Markov basis and Laplace filter. The final… More >
Login
Register
