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2 articles for “Multi spectral image denoising”
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A Novel Decomposable Pixel Component Analysis Algorithm for Automating Multispectral Satellite Image Denoising
Abstract: In comparison with the standard RGB or gray-scale images the usual multispectral images (MSI) is intended to convey high definition and an authentic representation for real world scenes to significantly enhance the performance measures of several other tasks involving with computer vision, segmentation of image, object extraction and object tagging operations. However, in practices a MSI image is always prone to corruption by various sources of noises while procuring the …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 2, Issue 3, 2014 · pp. 18–25 Read article
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Diffusion-Based Enhancement of Low-SNR Time- Frequency Signals
Abstract: Traditional enhancing techniques are useless in low signal-to-noise ratio (LSNR) situations because noise drastically interferes with communication signals. Based on an enhanced DiffBIR model, this paper suggests a dual-stage signal improvement approach that combines diffusion with deep learning. By combining the Inception module for multi-scale feature extraction with the Pixel Fusion Attention (PFA) module for significant region highlighting, the model improves signal recovery in the time- frequency domain. Experiments show …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 15–27 Read article