Segmentation is a process of separating the objects from background. Several GA-based approaches have been used to improve the quality of image segmentation in the past based on thresholds, edge detection, region and cluster detection and morphology. The proposed GA-based approach gives us good results for the segmentation of binary images using different image parameters namely the image block...

Cellular Automata (CA) have been considered one of the most pronounced parallel computational tools in the recent era of nature and bio-inspired computing. Taking advantage of their local connectivity, the simplicity of their design and their inherent parallelism, CA can be effectively applied to many image processing tasks. In this paper, a CA approach for efficient salt-n-pepper noise filteri...

In the paper a novel method for the estimation of the face recognition accuracy based on the modified Structural Similarity is presented. A typical application of the Structural Similarity index is related to the full-reference objective image quality assessment. Growing popularity of this metric is caused not only by the fact of its relatively low computational complexity but also by its sensi...

Complex coacervation is an electrostatically-driven phase separation phenomenon that is utilized in a wide range of everyday applications and is of great interest for the creation of self-assembled materials. Here, we utilized turbidity to characterize the effect of salt type on coacervate formation using two vinyl polyelectrolytes, poly(acrylic acid sodium salt) (pAA) and poly(allylamine hydro...

We propose a new approach to reduce speckle noise and enhance structures in speckle-corrupted images. It utilizes a mediananisotropic diffusion compound scheme. The median-filter-based reaction term acts as a guided energy source to boost the structures in the image being processed. In addition, it regularizes the diffusion equation to ensure the existence and uniqueness of a solution. We also ...

This paper proposes an additional ‘Median Layer’ to the existing Convolutional Neural Network (CNN).The work primarily focuses on removing ‘High Density Impulse Noise’ present in image. The proposed median layer performs filtering all feature channels. developed network is end-to-end that does not require any non-trivial preprocessing tasks. Based experiments performed, results show that, by in...

An automated binary change detection model using a threshold-based calibration approach was introduced in the study. The burdensome processes required in binary change detection, including calibration, calculation of accuracy, extraction of optimum threshold(s), generation of a binary change mask, and removal of “salt-and-pepper” noise were integrated and automated in the model. For practical p...

An Impulse noise detection & removal with adaptive filtering approach is proposed to restore images corrupted by salt & pepper noise. The proposed algorithm works well for suppressing impulse noise with noise density from 5 to 60% while preserving image details. The difference of current central pixel with median of local neighborhood pixels is used to classify the central pixel as noisy or noi...