Most digital cameras use an array of alternating color filters to capture the varied colors in a scene with a single sensor chip. Reconstruction of a full color image from such a color mosaic is what constitutes demosaicing. In this paper, a technique is proposed that performs this demosaicing in a way that incurs a very low computational cost. This is done through a (dual-tree complex) wavelet interpretation of the demosaicing problem. By using a novel locally adaptive approach for demosaicing (complex) wavelet coefficients, we show that many of the common demosaicing artifacts can be avoided in an efficient way. Results demonstrate that the proposed method is competitive with respect to the current state of the art, but incurs a lower computational cost. The wavelet approach also allows for computationally effective denoising or deblurring approaches.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3643977 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0061846 | PLOS |
Biomed Tech (Berl)
December 2024
66284 School of Design & Art, Shenyang Aerospace University, Shenyang, China.
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View Article and Find Full Text PDFSensors (Basel)
January 2025
College of Computer Science and Technology, Beihua University, No. 3999 East Binjiang Road, Jilin 132013, China.
Aeromagnetic surveying technology detects minute variations in Earth's magnetic field and is essential for geological studies, environmental monitoring, and resource exploration. Compared to conventional methods, residence time difference (RTD) fluxgate sensors deployed on unmanned aerial vehicles (UAVs) offer increased flexibility in complex terrains. However, measurement accuracy and reliability are adversely affected by environmental and sensor noise, including Barkhausen noise.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China.
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View Article and Find Full Text PDFEntropy (Basel)
January 2025
School of Computer Science, Guangdong Polytechnic Normal University, Guangzhou 510665, China.
Emotion recognition is an advanced technology for understanding human behavior and psychological states, with extensive applications for mental health monitoring, human-computer interaction, and affective computing. Based on electroencephalography (EEG), the biomedical signals naturally generated by the brain, this work proposes a resource-efficient multi-entropy fusion method for classifying emotional states. First, Discrete Wavelet Transform (DWT) is applied to extract five brain rhythms, i.
View Article and Find Full Text PDFHeliyon
January 2025
College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, 310027, China.
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