Simultaneous contrast improvement and denoising via diffusion related equations

Guillermo Sapiro; Vicent Caselles

doi:10.1117/12.216427

Simultaneous contrast improvement and denoising via diffusion related equations

Research output: Contribution to journal › Conference article › peer-review

Abstract

The explicit use of partial differential equations (PDE's) in image processing became a major topic of study in the last years. In this work we present an algorithm for histogram modification via PDE's. We show that the histogram can be modified to achieve any given distribution. The modification can be performed while simultaneously reducing noise. This avoids the noise sharpening effect in classical algorithms. The approach is extended to local contrast enhancement as well. A variational interpretation of the flow is presented and theoretical results on the existence of solutions are given.

Original language	English (US)
Pages (from-to)	342-353
Number of pages	12
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	2573
DOIs	https://doi.org/10.1117/12.216427
State	Published - Aug 11 1995
Externally published	Yes
Event	Vision Geometry IV 1995 - San Diego, United States Duration: Jul 9 1995 → Jul 14 1995

All Science Journal Classification (ASJC) codes

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

Keywords

Denoising
Histogram modification
Partial differential equations
Variational formulation

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10.1117/12.216427

Cite this

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abstract = "The explicit use of partial differential equations (PDE's) in image processing became a major topic of study in the last years. In this work we present an algorithm for histogram modification via PDE's. We show that the histogram can be modified to achieve any given distribution. The modification can be performed while simultaneously reducing noise. This avoids the noise sharpening effect in classical algorithms. The approach is extended to local contrast enhancement as well. A variational interpretation of the flow is presented and theoretical results on the existence of solutions are given.",

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author = "Guillermo Sapiro and Vicent Caselles",

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AU - Sapiro, Guillermo

AU - Caselles, Vicent

PY - 1995/8/11

Y1 - 1995/8/11

N2 - The explicit use of partial differential equations (PDE's) in image processing became a major topic of study in the last years. In this work we present an algorithm for histogram modification via PDE's. We show that the histogram can be modified to achieve any given distribution. The modification can be performed while simultaneously reducing noise. This avoids the noise sharpening effect in classical algorithms. The approach is extended to local contrast enhancement as well. A variational interpretation of the flow is presented and theoretical results on the existence of solutions are given.

AB - The explicit use of partial differential equations (PDE's) in image processing became a major topic of study in the last years. In this work we present an algorithm for histogram modification via PDE's. We show that the histogram can be modified to achieve any given distribution. The modification can be performed while simultaneously reducing noise. This avoids the noise sharpening effect in classical algorithms. The approach is extended to local contrast enhancement as well. A variational interpretation of the flow is presented and theoretical results on the existence of solutions are given.

KW - Denoising

KW - Histogram modification

KW - Partial differential equations

KW - Variational formulation

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DO - 10.1117/12.216427

M3 - Conference article

AN - SCOPUS:85079696663

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VL - 2573

SP - 342

EP - 353

JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

T2 - Vision Geometry IV 1995

Y2 - 9 July 1995 through 14 July 1995

ER -

Simultaneous contrast improvement and denoising via diffusion related equations

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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