Summary

Edited Journals

ICCK Contributions


Free Access | Research Article | 05 November 2025
Comparative Evaluation of Nearest Regularized Subspace and Machine Learning Techniques for Hyperspectral Image Classification
ICCK Transactions on Intelligent Systematics | Volume 2, Issue 4: 213-223, 2025 | DOI: 10.62762/TIS.2025.224024
Abstract
Hyperspectral imaging (HSI) has become a powerful remote sensing and material analysis tool because it can capture detailed spectral information in hundreds of adjacent bands. Nevertheless, the high dimensionality and redundancy in HSI data make precise and efficient classification challenging. This paper presents an extensive comparative study of both traditional and state-of-the-art Machine Learning algorithms for HSI classification. Classical classifiers like Support Vector Machines (SVM) and K-Nearest Neighbors (KNN) are compared with state-of-the-art methods like Collaborative and Sparse Representation-based approaches, Convolutional Recurrent Neural Networks (CRNN), Classification and... More >

Graphical Abstract
Comparative Evaluation of Nearest Regularized Subspace and Machine Learning Techniques for Hyperspectral Image Classification

Open Access | Research Article | 26 June 2025
Multi Focus Image Fusion using Image Enhancement Methods
ICCK Journal of Image Analysis and Processing | Volume 1, Issue 2: 57-72, 2025 | DOI: 10.62762/JIAP.2025.772403
Abstract
The challenge with multifocus images lies in different regions being in focus across various shots, resulting in some areas appearing blurry while others are sharp. This issue is prevalent in fields such as medical imaging, remote sensing, and photography, where clear and detailed images are essential. This project introduces a novel approach to multifocus image fusion by integrating the Marr--Hildreth edge detection technique with Discrete Cosine Transform (DCT), Stationary Wavelet Transform (SWT), and Discrete Wavelet Transform (DWT). The Marr--Hildreth algorithm detects edges by identifying zero-crossings in the Laplacian of a Gaussian-blurred image, effectively highlighting areas with si... More >

Graphical Abstract
Multi Focus Image Fusion using Image Enhancement Methods

Open Access | Research Article | 14 March 2025 | Cited: 1 , Scopus 1
High-Quality Multi-Focus Image Fusion: A Comparative Analysis of DCT-Based Approaches with Their Variants
ICCK Journal of Image Analysis and Processing | Volume 1, Issue 1: 27-35, 2025 | DOI: 10.62762/JIAP.2024.764051
Abstract
Image fusion, especially in the context of multi-focus image fusion, plays a crucial role in digital image processing by enhancing the clarity and detail of visual content through the combination of multiple source images. Traditional spatial domain methods often suffer from issues like spectral distortion and low contrast, which has led researchers to explore techniques in the frequency domain, such as the Discrete Cosine Transform (DCT). DCT-based methods are particularly valued for their computational efficiency, making them a strong alternative, especially in applications like image compression and fusion. This study focuses on DCT-based approaches, including variants that incorporate Si... More >

Graphical Abstract
High-Quality Multi-Focus Image Fusion: A Comparative Analysis of DCT-Based Approaches with Their Variants