Infrared and Laser Engineering 

About: Infrared and Laser Engineering is an academic journal published by Shanghai Institute of Optics and Fine Mechanics. The journal publishes majorly in the area(s): Laser & Lidar. It has an ISSN identifier of 1007-2276. Over the lifetime, 2644 publications have been published receiving 5202 citations. The journal is also known as: Infrared & Laser Engineering.

Infrared image adaptive inverse histogram enhancement technology

Abstract: In infrared images, when the traditional histogram equalizes the image, the detail pixels are easily immerged by the background pixels, resulting in the image being too bright and too dark. Based on this situation, an adaptive inverse histogram equalization algorithm was proposed in this paper. The algorithm enhanced image details by inverse statistics, adaptive selection threshold and segmentation mapping. Compared with the traditional histogram equalization algorithm, the inverse histogram equalization algorithm significantly improve the image visual effect in different gray level distributions and enhance the details of different areas of the image to different degrees. Moreover, under the premise of achieving better image processing effects, this algorithm can still guarantee real-time performance and high efficiency by optimizing calculation methods, and is suitable for FPGA hardware transplantation.

Algorithm of laser spot detection based on circle fitting

Abstract: Laser spot detection is the key technique used in optical measurement. The precision and speed of the detection algorithm affect those of the optical measurement system directly. The traditional algorithms such as gravity model, Hough transform are unsatisfactory under some conditions. The laser spot detection algorithm referred in this paper is based on the LSM (least square method), and a circle is adopted to approximate the edge of the laser spot. Not only the center and radius can be detected simultaneously, but also the orientation precision is in the order of sub\|pixels, and the speed is fast. The algorithm is suitable for real\|time optical measurement.

New enhancement algorithm for infrared image based on double plateaus histogram

Abstract: The characteristics of the infrared dim-small targets images were analyzed.A new contrast enhancement algorithm was presented based on double plateaus histogram equalization.By setting a higher threshold value as the upper limit,the algorithm could constrain the background and noises.By setting a lower threshold value as the lower limit,the algorithm could magnify the dim-small targets and the details of the image.Then,the gray intervals of the histogram were equalized.The disadvantages of histogram equalization were overcame with the proposed method.Compared with the algorithm based on single plateau histogram,the new method can enhance image contrast,and preserve image detail simultaneously.

Analysis and processing of CCD noise

Abstract: In order to improve CCD performance, the noise composition in CCD image is analyzed according to the operating principle of CCD, and CCD noise is categorized Correspending measures are introduced to deal with different noise Signal processing schemes of double-correlated sampling,dual slope integration and clamp sample are given to eliminate readout noise in this paper As a result, the SNR of CCD is improved

Approach on image contrast enhancement based on wavelet transform

Abstract: Image enhancement is an important issue of image processing technique, which is used to improve the visual quality of image Pointing at the shortcoming of noise over\|enhancement of traditional algorithm, a wavelet\|based approach for image contrast enhancement is proposed On the basis of taking full advantage of multiscale wavelet analysis, firstly the algorithm takes a step of wavelet shrinkage and then differently enhances the coefficients at each scale To achieve a better visual effect, the algorithm takes in account human visual system while enhancing the wavelet coefficients Experiment of the algorithm demonstrates that the algorithm avoids over\|enhancement of noise while enhancing contrast of the image with good visual effect \;