Practical implementation of LMMSE demosaicing using luminance and chrominance spaces
Computer Vision and Image Understanding
Demosaicking based on optimization and projection in different frequency bands
Journal on Image and Video Processing - Color in Image and Video Processing
Color in image and video processing: most recent trends and future research directions
Journal on Image and Video Processing - Color in Image and Video Processing
Additive spread-spectrum watermark detection in demosaicked images
Proceedings of the 11th ACM workshop on Multimedia and security
PCA-based spatially adaptive denoising of CFA images for single-sensor digital cameras
IEEE Transactions on Image Processing
Self-similarity driven color demosaicking
IEEE Transactions on Image Processing
Joint demosaicking and denoising with space-varying filters
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Color image demosaicking: An overview
Image Communication
Novel color demosaicking for noisy color filter array data
Signal Processing
Computational plenoptic imaging
ACM SIGGRAPH 2012 Courses
Simplified noise model parameter estimation for signal-dependent noise
Signal Processing
A unified framework for multi-sensor HDR video reconstruction
Image Communication
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The output image of a digital camera is subject to a severe degradation due to noise in the image sensor. This paper proposes a novel technique to combine demosaicing and denoising procedures systematically into a single operation by exploiting their obvious similarities. We first design a filter as if we are optimally estimating a pixel value from a noisy single-color (sensor) image. With additional constraints, we show that the same filter coefficients are appropriate for color filter array interpolation (demosaicing) given noisy sensor data. The proposed technique can combine many existing denoising algorithms with the demosaicing operation. In this paper, a total least squares denoising method is used to demonstrate the concept. The algorithm is tested on color images with pseudorandom noise and on raw sensor data from a real CMOS digital camera that we calibrated. The experimental results confirm that the proposed method suppresses noise (CMOS/CCD image sensor noise model) while effectively interpolating the missing pixel components, demonstrating a significant improvement in image quality when compared to treating demosaicing and denoising problems independently