1. Bio-inspired Computing Paradigm for Periodic‎ Noise Reduction in Digital Images

N. Alibabaie; A.M. Latif

Volume 9, Issue 1 , Winter 2021, , Pages 19-29

http://dx.doi.org/10.22044/jadm.2020.9358.2071

Abstract
  Periodic noise reduction is a fundamental problem in image processing, which severely affects the visual quality and subsequent application of the data. Most of the conventional approaches are only dedicated to either the frequency or spatial domain. In this research, we propose a dual-domain approach ...  Read More

2. Joint Burst Denoising and Demosaicking via Regularization and an Efficient Alignment

R. Azizi; A. M. Latif

Volume 8, Issue 4 , Autumn 2020

http://dx.doi.org/10.22044/jadm.2020.9193.2055

Abstract
  In this work, we show that an image reconstruction from a burst of individually demosaicked RAW captures propagates demosaicking artifacts throughout the image processing pipeline. Hence, we propose a joint regularization scheme for burst denoising and demosaicking. We model the burst alignment functions ...  Read More

H.3.15.3. Evolutionary computing and genetic algorithms
3. Tuning Shape Parameter of Radial Basis Functions in Zooming Images using Genetic Algorithm

A.M Esmilizaini; A.M Latif; Gh. Barid Loghmani

Volume 6, Issue 2 , Summer 2018, , Pages 251-262

http://dx.doi.org/10.22044/jadm.2017.4815.1575

Abstract
  Image zooming is one of the current issues of image processing where maintaining the quality and structure of the zoomed image is important. To zoom an image, it is necessary that the extra pixels be placed in the data of the image. Adding the data to the image must be consistent with the texture in ...  Read More