Detection of Partial Invisible Objects in Images using Histogram Equalization

Abstract

The current paper proposes recognition of partially invisible objects in images using image enhancement techniques. The problem mainly arises in night vision images which comprise poor contrast standards. Also during daytime, the object which is captured under sunlight is the lone survivor and the rest of information is not captured by camera properly. Image enhancement techniques to improve visual quality have been popularized with the proliferation of digital imagery and computers. Histogram Equalization (HE) is a versatile image improvement technique that can be incorporated for converting the partial visible objects/invisible objects into a proper vision. Further for enriching the information in image obtained by the HE image, a Contrast Limited Adaptive Histogram Equalization (CLAHE) is incorporated and finally for smoothing purpose, the image thus obtained is passed through a Gaussian filter. Results on various set of images show that above two techniques HE and CLAHE along with a Gaussian filter significantly improve the quality of image and hence assist to discover the partially visible/invisible objects.

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“…Histogram Equalization achieves contrast enhancement by equalizing the image intensities. Multiple works have successfully used this technique for vision enhancement [69,55] and object detection [70], and medical image processing [71]. By redistributing the pixels between the highest and the darkest portions of an image, we make a dark image (underexposed) less dark and a bright image (overexposed) less bright.…”