Fundamentals of digital image processing
Fundamentals of digital image processing
Digital image processing
Detail-preserving median based filters in image processing
Pattern Recognition Letters
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Adaptive fuzzy switching filter for images corrupted by impulse noise
Pattern Recognition Letters
Noise reduction by fuzzy image filtering
IEEE Transactions on Fuzzy Systems
A new efficient approach for the removal of impulse noise from highly corrupted images
IEEE Transactions on Image Processing
Tri-state median filter for image denoising
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
On the origin of the bilateral filter and ways to improve it
IEEE Transactions on Image Processing
Selective removal of impulse noise based on homogeneity level information
IEEE Transactions on Image Processing
Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization
IEEE Transactions on Image Processing
A universal noise removal algorithm with an impulse detector
IEEE Transactions on Image Processing
A fuzzy impulse noise detection and reduction method
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Universal Impulse Noise Filter Based on Genetic Programming
IEEE Transactions on Image Processing
Multiresolution Bilateral Filtering for Image Denoising
IEEE Transactions on Image Processing
Adaptive median filters: new algorithms and results
IEEE Transactions on Image Processing
A versatile denoising method for images contaminated with Gaussian noise
Proceedings of the CUBE International Information Technology Conference
Modified directional weighted filter for removal of salt & pepper noise
Pattern Recognition Letters
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In this paper, we propose a switching bilateral filter (SBF) with a texture and noise detector for universal noise removal. Operation was carried out in two stages: detection followed by filtering. For detection, we propose the sorted quadrant median vector (SQMV) scheme, which includes important features such as edge or texture information. This information is utilized to allocate a reference median from SQMV, which is in turn compared with a current pixel to classify it as impulse noise, Gaussian noise, or noise-free. The SBF removes both Gaussian and impulse noise without adding another weighting function. The range filter inside the bilateral filter switches between the Gaussian and impulse modes depending upon the noise classification result. Simulation results show that our noise detector has a high noise detection rate as well as a high classification rate for salt-and-pepper, uniform impulse noise and mixed impulse noise. Unlike most other impulse noise filters, the proposed SBF achieves high peak signal-to-noise ratio and great image quality by efficiently removing both types of mixed noise, salt-and-pepper with uniform noise and salt-and-pepper with Gaussian noise. In addition, the computational complexity of SBF is significantly less than that of other mixed noise filters.