Real and complex analysis, 3rd ed.
Real and complex analysis, 3rd ed.
Kendall's advanced theory of statistics
Kendall's advanced theory of statistics
Recovering high dynamic range radiance maps from photographs
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Determining Image Origin and Integrity Using Sensor Noise
IEEE Transactions on Information Forensics and Security
Image denoising using scale mixtures of Gaussians in the wavelet domain
IEEE Transactions on Image Processing
Image denoising using total least squares
IEEE Transactions on Image Processing
Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries
IEEE Transactions on Image Processing
Pointwise Shape-Adaptive DCT for High-Quality Denoising and Deblocking of Grayscale and Color Images
IEEE Transactions on Image Processing
Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering
IEEE Transactions on Image Processing
Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data
IEEE Transactions on Image Processing
High dynamic range image hallucination
EGSR'07 Proceedings of the 18th Eurographics conference on Rendering Techniques
A unified framework for multi-sensor HDR video reconstruction
Image Communication
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We study the denoising of signals from clipped noisy observations, such as digital images of an under- or over-exposed scene. From a precise mathematical formulation and analysis of the problem, we derive a set of homomorphic transformations that enable the use of existing denoising algorithms for non-clipped data (including arbitrary denoising filters for additive independent and identically distributed, i.i.d., Gaussian noise). Our results have general applicability and can be ''plugged'' into current filtering implementations, to enable a more accurate and better processing of clipped data. Experiments with synthetic images and with real raw data from charge-coupled device (CCD) sensor show the feasibility and accuracy of the approach.