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Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

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Realistic Image Rendition Using a Variable Exponent Functional Model for Retinex.

Zeyang Dou¹, Kun Gao², Bin Zhang³

¹Key Laboratory of Photoelectronic Imaging Technology and System, Ministry of Education of China, Beijing Institute of Technology, Beijing 100081, China. douzeyang123@163.com.

Sensors (Basel, Switzerland)

|June 25, 2016

Summary

This summary is machine-generated.

This study introduces a new Retinex model to fix images with uneven lighting. The variable exponent model effectively removes illumination issues and reduces unwanted halo effects for better image quality.

Keywords:

Retinex halo artifact illumination removal image rendition variable exponent functional

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Area of Science:

Computer Vision
Image Processing
Computational Imaging

Background:

Realistic image rendition aims to restore images captured under challenging, non-uniform lighting conditions.
Imperfect illumination often leads to degraded image quality, characterized by high contrast and low signal-to-noise ratio (SNR).

Purpose of the Study:

To propose a novel variable exponent functional model for Retinex theory.
To address the limitations of existing models in handling non-uniform illumination and reducing halo artifacts.
To enhance the quality of images acquired under adverse lighting scenarios.

Main Methods:

Modification of the standard illumination assumption in Retinex theory.
Development of a variable exponent functional model.
Theoretical derivation and mathematical analysis of the proposed model.
Experimental validation of the model's performance.

Main Results:

The proposed variable exponent Retinex model effectively removes non-uniform illumination.
The model successfully reduces halo artifacts, a common issue in image enhancement.
Experimental results demonstrate significant improvements in image quality compared to existing methods.

Conclusions:

The variable exponent functional model offers a robust solution for non-uniform illumination correction.
The proposed method enhances realistic image rendition by improving contrast and reducing noise.
This work contributes a valuable tool for image processing applications requiring high-quality visual output.