Image Processing Reference
Besides above applications, there are other applications. Because this algorithm uses the prop-
erties of the image itself. We process overexposed images by means of this algorithm and get
good results. Our algorithm avails several applications due to its fundamentality and the spe-
cial properties in processing natural images.
Overexposed images often have high brightness, low contrast, and invisible details. This al-
gorithm can effectively restore the contrast and brightness to a suitable standard for human
senses by means of the transformation between the original image and illumination image.
The processing results of overexposed images are listed (seen in Figures 9 - 10 ) . Panel (a) is the
original image and (b) displays the enhanced image by the proposed algorithm in this article.
It can be clearly seen from the figures that this algorithm has a good restoration of overex-
posed images, making the images more in line with human senses. This approach enhances
signiicant edges, making structures visually pleasing.
FIGURE 9 Scene 6.
FIGURE 10 Scene 7.
6 The conclusion
In this article we present an efective algorithm for enhancing the nightime image. In our al-
gorithm, we propose a statistical law to present the relation of the original image and illumin-
ation image. Using this statistical law and retinex theory, we can accurately and quickly get
the resulting image. The algorithm is validated through subjective and objective evaluation,
which shows it can eliminate the “halo effect,” enhance the image contrast, recover image de-
tails and have low time complexity. In summary, our algorithm is effective to complete the
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