In view of the histogram equalizing algorithm to enhance image in digital
image processing, an Infrared Image Gray adaptive adjusting Enhancement Algorithm
Based on Gray Redundancy Histogram-dealing Technique is proposed. The algorithm
is based on the determination of the entire image gray value, enhanced or lowered the
image’s overall gray value by increasing appropriate gray points, and then use
gray-level redundancy HE method to compress the gray-scale of the image. The
algorithm can enhance image detail information. Through MATLAB simulation, this
paper compares the algorithm with the histogram equalization method and the
algorithm based on gray redundancy histogram-dealing technique
, and verifies the effectiveness of the algorithm.
The ground temperature variation in certain place of Xinjiang during summer daytime was studied through
simulative calculation. The ground was hypothesized as a uniform medium with a infinite flat surface, which simply the
temperature variation of earth surface as a one dimensional transitional heat conduct model. Then, the calculation
formula of every radiation part such as the sun direct radiation and scatter radiation, atmosphere long wave radiation,
atmosphere convective heat conduction were analyzed and established. Also, every input parameters and boundary
conditions were made. Finally, the model was constructed and calculated using Comsol software. The calculation result
shows that the model being constructed, the parameters and boundary conditions being input are correct.
Based on the analysis of the characteristics of infrared dim small target under complex cloud background, A detection algorithm is proposed for infrared dim small target. Firstly, median filtering algorithm is employed to remove the noise effectively. Secondly, according to the characteristics of the cloud background and targets, a frequency-domain processing method based on Fourier transform and second-order Butterworth high pass filtering is proposed. The cutoff frequency of the filter is adaptively decided by establishing the relationship between the background complexity and the cutoff frequency. Lastly, target detection is achieved by threshold segmentation. Experiments showed that the algorithm can effectively detect infrared dim small target under complex cloud background.
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