基于物理模型與邊界約束的低照度圖像增強(qiáng)算法

陳勇; 詹帝; 劉煥淋

doi:10.11999/JEIT170267

基于物理模型與邊界約束的低照度圖像增強(qiáng)算法

doi: 10.11999/JEIT170267 cstr: 32379.14.JEIT170267

基金項(xiàng)目:

國(guó)家自然科學(xué)基金(60975008)，重慶市研究生科研創(chuàng)新項(xiàng)目(CYS17235)

計(jì)量
- 文章訪問數(shù): 1291
- HTML全文瀏覽量: 164
- PDF下載量: 307
- 被引次數(shù): 0
出版歷程
- 收稿日期: 2017-03-29
- 修回日期: 2017-09-18
- 刊出日期: 2017-12-19

Enhancement Algorithm for Low-lighting Images Based on Physical Model and Boundary Constraint

(Key Laboratory of Industrial Internet of Things and Network Control, Ministry of Education, Chongqing University of Posts and Telecommunications, Chongqing 400065, China)

Funds:

The National Natural Science Foundation of China (60975008), Chongqing Graduate Student Science Research Innovation Foundation (CYS17235)

摘要

摘要: 針對(duì)低照度下圖像降質(zhì)嚴(yán)重的問題，該文提出一種基于邊界約束與圖像亮度的低照度圖像增強(qiáng)算法。該算法首先通過改進(jìn)的邊界約束對(duì)偽霧圖進(jìn)行透射率估計(jì)，并對(duì)其進(jìn)行優(yōu)化；同時(shí)從偽霧圖霧的形成原理出發(fā)，利用低照度圖像的亮度分量進(jìn)行偽霧圖大氣光值的估計(jì)；最后將增強(qiáng)后的偽霧圖反轉(zhuǎn)，即得到增強(qiáng)后的低照度圖像。實(shí)驗(yàn)結(jié)果表明，針對(duì)低照度下的圖像，該算法可以有效地提升對(duì)比度和亮度，過增強(qiáng)現(xiàn)象得到改善；效果優(yōu)于對(duì)比算法，且復(fù)雜度低。
- 低照度圖像增強(qiáng) /
- 偽霧圖 /
- 邊界約束 /
- 物理模型
Abstract: The aim of this paper is to achieve a low-lighting image enhancement method by using the similarity between fog image and inverted low illumination image. The transmittance estimation of the pseudo-fog image is estimated by the improved boundary constraint, and then it is optimized. Based on the formation principle of pseudo fog, the light intensity of pseudo fog map is estimated by using the brightness component of low illumination image. The enhanced pseudo fog image is reversed to obtain the enhanced low illumination image. Extensive experimental results using natural low-lighting images indicate that the proposed method perform better than contemporary algorithms in terms of several metrics, including the intensity, the contrast. The proposed algorithm can effectively suppress the wrong phenomenon caused by enhanced with low complexity.
- Low-lighting image enhancement /
- Pseudo-fog image /
- Boundary constraint /
- Physical model

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