ICCK Journal of Image Analysis and Processing

Aims & Scope

The ICCK Journal of Image Analysis and Processing (JIAP) is a peer-reviewed, open-access journal dedicated to advancing fundamental theory, methodological innovation, and practical applications in image and video analysis, computer vision, and computational imaging. The journal aims to provide a high-quality international platform for researchers and practitioners to disseminate novel methodologies, algorithms, and systems that address fundamental challenges in visual data understanding and processing. The scope of the Journal includes, but is not limited to: Image acquisition, sensing, and computational imaging systems Image enhancement, restoration, denoising, and super-resolution Image segmentation, object detection, and scene understanding Feature extraction, pattern recognition, and visual representation learning Computer vision methods for image and video analysis Deep learning and machine learning for image processing applications Multimodal and multisensor data fusion techniques Medical image analysis and biomedical imaging systems Remote sensing, hyperspectral imaging, and geospatial image analysis Industrial inspection, quality control, and automated visual systems Surveillance systems and human activity recognition in videos Image forgery detection, authentication, and digital forensics Real-time image processing and edge/embedded vision systems Explainable AI and interpretable deep learning in imaging applications Applications in agriculture, environmental monitoring, and smart systems Emerging applications including IoT-based imaging and intelligent perception systems

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Subject Classification