Multi-Exposure Image Fusion Based on Patch using Global and Local Characteristics

  • Kim, Jihwan
  • Choi, Hyunho
  • Jeong, Je chang
Citations

SCOPUS

1

초록

In this paper, we propose an algorithm that improves the weight map part consisting of signal strength, signal structure, and mean intensity. The patch-based conventional weight map causes the brightness of the image to be shifted to one side, resulting in loss of image information, unexpected artifacts, and an overall unbalance in image brightness. In this study, we propose a novel algorithm by improving the weight map. First, the order-statistic filter using maximum values. Second, the unsharp masking filter using Laplacian. Third, the linear combination using gamma transformation. The proposed algorithm prevents the loss of image information by reducing the over-saturation of the image, accurate representation of dark and bright areas by increasing contrast, and preserve the detail such as the edge. Through subjective and objective experimental results, it is confirmed that the proposed algorithm shows better performance than the conventional algorithms.

키워드

gamma transformationhigh dynamic rangemulti-exposure image fusionorder-statisticsunsharp maskingEdge detectionLinear transformationsLuminanceMathematical transformationsSignal processinggamma transformationHigh dynamic rangeMulti-exposure imagesOrder statisticsUnsharp maskingImage fusion
제목
Multi-Exposure Image Fusion Based on Patch using Global and Local Characteristics
저자
Kim, JihwanChoi, HyunhoJeong, Je chang
DOI
10.1109/TSP.2018.8441463
발행일
2018-08
유형
Conference Paper
저널명
2018 41st International Conference on Telecommunications and Signal Processing, TSP 2018
페이지
112 ~ 115