Multiscale patch-based contrast measure for small infrared target detection

To efficiently enhance images, a novel algorithm using multi scale image features extracted by top-hat transform is proposed in this paper. Firstly, the multi scale bright and dim regions are extracted through top-hat transform using structuring elements with the same shape and increasing sizes. Then, two types of multi scale image features, which are the multi scale bright and dim image regions at each scale and the multi scale image details between neighboring scales, are extracted and used to form the final extracted bright and dim image regions. Finally, the image is enhanced through enlarging the contrast between the final extracted bright and dim image features. Experimental results on images from different applications verified that the proposed algorithm could efficiently enhance the contrast and details of image, and produce few noise regions.

Image enhancement using multi scale image features extracted by top-hat transform

Infrared image enhancement through contrast enhancement by using multiscale new top-hat transform

Fusion of infrared and visual images is an important research area in image analysis. The purpose of infrared and visual image fusion is to combine the image information of the original images into the final fusion result. So, it is crucial to effectively extract the image information of the original images and reasonably combine them into the final fusion image. To achieve this purpose, an algorithm by using multi scale center-surround top-hat transform through region extraction is proposed in this paper. Firstly, multi scale center-surround top-hat transform is discussed and used to extract the multi scale bright and dim image regions of the original images. Secondly, the final extracted image regions for image fusion are constructed from the extracted multi scale bright and dim image regions. Finally, after a base image is calculated from the original images, the final extracted image regions are combined into the base image through a power strategy to form the final fusion result. Because the image information of the original images are well extracted and combined, the proposed algorithm is very effective for image fusion. Comparison experiments have been performed on different image sets, and the results verified the effectiveness of the proposed algorithm.

Fusion of infrared and visual images through region extraction by using multi scale center-surround top-hat transform

Technical Communication: Infrared small target enhancement and detection based on modified top-hat transformations

Enhancement of dim small target through modified top-hat transformation under the condition of heavy clutter

Enhanced detectability of point target using adaptive morphological clutter elimination by importing the properties of the target region

Survey on Dim Small Target Detection in Clutter Background: Wavelet, Inter-Frame and Filter Based Algorithms

To reduce the influences of the dim target intensity and heavy clutter on infrared small target detection and tracking, a
novel algorithm is presented in this paper. The algorithm proposes a modified top-hat transformation by importing the
property of the small target region firstly, which largely enhances the dim target and apparently suppresses the heavy
clutter. Consequently, the potential targets are easy to be segmented by the iterative thresholding method. After
decreasing the false alarms through the dilation cumulation, the real target and the trajectory are correctly given by using
the data association formed by the motion property of the real target. Various experiments verified that the proposed
algorithm was efficient and robust for dim target detection and tracking under the condition of heavy clutter.

Ting Jin

Papers

Enhancement of dim small target through modified top-hat transformation under the condition of heavy clutter

Enhanced detectability of point target using adaptive morphological clutter elimination by importing the properties of the target region

Survey on Dim Small Target Detection in Clutter Background: Wavelet, Inter-Frame and Filter Based Algorithms

Infrared small target detection and tracking under the conditions of dim target intensity and clutter background

Analysis of top-hat selection transformation and some modified top-hat transformations