Degradation of turbid images based on the adaptive logarithmic algorithm

Yu Yi Liao, Shen-Chuan Tai, Jzau Sheng Lin, Ping Jui Liu

Research output: Contribution to journalArticle

2 Citations (Scopus)


Turbidity such as fog, mist, haze, and smoke progressively reduces image contrast and visibility with increasing distance. In this paper, we propose an algorithm to degrade the turbid degree from the turbid image. The turbidity can be considered as a kind of noise. The basic assumption of the proposed algorithm is that an image consists of a reference intensity level and a characteristic intensity level. The reference intensity level is considered as general or background intensity level and it can be obtained by a low pass filter. The characteristic intensity level can be calculated by subtracting the reference intensity level from the original intensity level in the given image. The human eye has a logarithmic intensity response so the target intensity level will be created by the adaptive logarithmic function to approach the human vision. The turbid image will be degraded by transforming the characteristic intensity level into the target intensity level according to the proportion of the reference intensity level to the chosen target intensity level. The experimental results show the varied degraded turbid image as well as compared with other algorithms.

Original languageEnglish
Pages (from-to)1259-1269
Number of pages11
JournalComputers and Mathematics with Applications
Issue number5
Publication statusPublished - 2012 Sep 1

All Science Journal Classification (ASJC) codes

  • Modelling and Simulation
  • Computational Theory and Mathematics
  • Computational Mathematics

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