Netinfo Security ›› 2018, Vol. 18 ›› Issue (2): 54-60.doi: 10.3969/j.issn.1671-1122.2018.02.008

• Orginal Article • Previous Articles     Next Articles

An Adaptive Adjusting Kernel Function-Based Extraction Method for Image Salient Area

Hongtao GAO1(), Wei LU2, Yuwang YANG2   

  1. 1. Department of Cyber Crime Investigation, Criminal Investigation Police University of China, Shenyang Liaoning 110035, China
    2. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing Jiangsu 210094, China
  • Received:2017-12-31 Online:2018-02-20 Published:2020-05-11

Abstract:

Existing visual area detection technology was often used for noise-free image, and the impact of noise on the detection technology was not analyzed. A new visual salient area detection method for noisy image was proposed in this paper. The adaptive kernel adjusting function in visual area detection was used in our method and the salient property was determined by the dissimilarities between a center patch around that pixel and other patches. The dissimilarity was measured as a decreasing function as adaptive kernel regression. At last, the visual salient area was obtained by multi-scale process. In order to demonstrate the feasibility of our approach, several simulation experiments were done. A good effect was obtained in Visual area detection experiments on noise-free images. Compared with two proposed methods for noisy images, our method owned strong anti-noise characteristics and strong robustness.

Key words: visual salient area, adaptive adjusting kernel function, image noise, multi-scale process

CLC Number: