A Fast Algorithm for Exact Histogram Specification. Simple Extension to Colour Images

Autor: Mila Nikolova
Přispěvatelé: Centre de Mathématiques et de Leurs Applications (CMLA), École normale supérieure - Cachan (ENS Cachan)-Centre National de la Recherche Scientifique (CNRS), 'This work benefited from the support of the 'FMJH Program Gaspard Monge in optimization and operation research', and from the support to this program from EDF.'
Rok vydání: 2013
Předmět:
Color image enhancement
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
02 engineering and technology
Exact histogram specification
Image (mathematics)
Variational methods
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
Fast smooth convex nonlinear minimization
Histogram
0202 electrical engineering
electronic engineering
information engineering
Mathematics
Discrete mathematics
Pixel
Total strict ordering
Minimizer analysis
Process (computing)
Histogram matching
Gamut preservation
Simple extension
Fast algorithm
020202 computer hardware & architecture
Variational method
020201 artificial intelligence & image processing
Fixed point algorithm
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Algorithm
Hue preservation
Smoothed ℓ1-TV functionals
[MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA]
Zdroj: Lecture Notes in Computer Science ISBN: 9783642382666
SSVM
Book Chapter Pages 174-185 A Fast Algorithm for Exact Histogram Specification. Simple Extension to Colour Images
Book Chapter Pages 174-185 A Fast Algorithm for Exact Histogram Specification. Simple Extension to Colour Images, 7893, Springer, pp.174-185, 2013, Lecture Notes in Computer Science, 978-3-642-38266-6. ⟨10.1007/978-3-642-38267-3⟩
DOI: 10.1007/978-3-642-38267-3_15
Popis: International audience; In [12] a variational method using C2-smoothed ℓ1-TV functionals was proposed to process digital (quantized) images so that the obtained minimizer is quite close to the input image but its pixels are all different from each other. These minimizers were shown to enable exact histogram specification outperforming the state-of-the-art methods [6], [19] in terms of faithful total strict ordering. They need to be computed with a high numerical precision. However the relevant functionals are difficult to minimize using standard tools because their gradient is nearly flat over vast regions. Here we present a specially designed fixed-point algorithm enabling to attain the minimizer with remarkable speed and precision. This variational method applied with the new proposed algorithm is actually the best way (in terms of quality and speed) to order the pixels in digital images. This assertion is corroborated by exhaustive numerical tests. We extend the method to color images where the luminance channel is exactly fitted to a prescribed histogram. We propose a new fast algorithm to compute the modified color values which preserves the hue and do not yield gamut problem. Numerical tests confirm the performance of the latter algorithm.
Databáze: OpenAIRE
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