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Comparative analysis of different methods for image enhancement 被引量:4
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作者 吴笑峰 胡仕刚 +4 位作者 赵瑾 李志明 李劲 唐志军 席在芳 《Journal of Central South University》 SCIE EI CAS 2014年第12期4563-4570,共8页
Image enhancement technology plays a very important role to improve image quality in image processing. By enhancing some information and restraining other information selectively, it can improve image visual effect. T... Image enhancement technology plays a very important role to improve image quality in image processing. By enhancing some information and restraining other information selectively, it can improve image visual effect. The objective of this work is to implement the image enhancement to gray scale images using different techniques. After the fundamental methods of image enhancement processing are demonstrated, image enhancement algorithms based on space and frequency domains are systematically investigated and compared. The advantage and defect of the above-mentioned algorithms are analyzed. The algorithms of wavelet based image enhancement are also deduced and generalized. Wavelet transform modulus maxima(WTMM) is a method for detecting the fractal dimension of a signal, it is well used for image enhancement. The image techniques are compared by using the mean(μ),standard deviation(?), mean square error(MSE) and PSNR(peak signal to noise ratio). A group of experimental results demonstrate that the image enhancement algorithm based on wavelet transform is effective for image de-noising and enhancement. Wavelet transform modulus maxima method is one of the best methods for image enhancement. 展开更多
关键词 image enhancement wavelet transform histogram equalization unsharp masking(UM) modulus maxl mum threshold
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TransHist:Occlusion-robust shape detection in cluttered images 被引量:1
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作者 Chu Han Xueting Liu +1 位作者 Lok Tsun Sinn Tien-Tsin Wong 《Computational Visual Media》 CSCD 2018年第2期161-172,共12页
Shape matching plays an important role in various computer vision and graphics applications such as shape retrieval, object detection, image editing,image retrieval, etc. However, detecting shapes in cluttered images ... Shape matching plays an important role in various computer vision and graphics applications such as shape retrieval, object detection, image editing,image retrieval, etc. However, detecting shapes in cluttered images is still quite challenging due to the incomplete edges and changing perspective. In this paper, we propose a novel approach that can efficiently identify a queried shape in a cluttered image. The core idea is to acquire the transformation from the queried shape to the cluttered image by summarising all pointto-point transformations between the queried shape and the image. To do so, we adopt a point-based shape descriptor, the pyramid of arc-length descriptor(PAD),to identify point pairs between the queried shape and the image having similar local shapes. We further calculate the transformations between the identified point pairs based on PAD. Finally, we summarise all transformations in a 4 D transformation histogram and search for the main cluster. Our method can handle both closed shapes and open curves, and is resistant to partial occlusions. Experiments show that our method can robustly detect shapes in images in the presence of partial occlusions, fragile edges, and cluttered backgrounds. 展开更多
关键词 shape matching shape detection transformation histogram
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