Duo to infrared image with low contrast, big noise and unclear visual effect, target is very difficult to observed and identified. This paper presents an improved infrared image detail enhancement algorithm based on adaptive histogram statistical stretching and gradient filtering (AHSS-GF). Based on the fact that the human eyes are very sensitive to the edges and lines, the author proposed to extract the details and textures by using the gradient filtering. New histogram could be acquired by calculating the sum of original histogram based on fixed window. With the minimum value for cut-off point, author carried on histogram statistical stretching. After the proper weights given to the details and background, the detail-enhanced results could be acquired finally. The results indicate image contrast could be improved and the details and textures could be enhanced effectively as well.
Step frequency signal is one of the more commonly used radar signal for high range resolution, it commonly used in radar target recognition. The wavelength of Terahertz signal is shorter than that of the microwave, so it is easy to realize the high range resolution. The paper first introduces the step frequency signal to obtain the one-dimensional distance image, and analyze the principle of high resolution range profiles of step frequency radar. Then, the 0.2THz step frequency radar systems are introduced. Finally, the high resolution range profiles are achieved by the simulation of Matlab. The simulation results show that the step frequency THz radar can reach centimeter level high resolution on stationary targets. For moving targets exist distance divergence and coupling shift. With greater speed, the greater the distortion.
Compared with traditional microwave and millimeter wave radars, Terahertz radar has wide signal bandwidth and a very narrow antenna beam, which is beneficial to the realization of high resolution imaging. And as an instantaneous narrowband and synthetic wideband waveform, stepped frequency radar signal has been widely exploited in many applications, since it allows high range resolution with modest requirements of the system bandwidth. As an instantaneous narrowband and synthetic wideband waveform, stepped frequency radar signal has been widely exploited in many applications, since it allows high range resolution with modest requirements of the system bandwidth. This paper presents the design of a 0.2THz stepped frequency imaging radar system with operating bandwidth of 12 GHz, thus, a theoretical range resolution below 1.25 cm. The simulation of the system is implemented by using system design parameters. An experimental trial has been performed, and one-dimensional range profile of the stationary target is obtained by Imaging Experiment using THz radar. Results show that the THz radar imaging system could achieve the target detection and centimeter-level range resolution.
Electronic image stabilization, a new generation of image stabilization technology, obtains distinct and stable image
sequences by detecting inter-frame offset of image sequences and compensating by way of image processing. As a highprecision
image processing algorithm, SIFT can be applied to object recognition and image matching, however, it is the
extremely low processing speed that makes it not applicable in electronic image stabilization system which is strict with
speed. Against the low speed defect of SIFT algorithm, this paper presents an improved SIFT algorithm aiming at
electronic image stabilization system, which combines SIFT algorithm with Harris algorithm. Firstly, Harris operator is
used to extract the corners out of two frames as feature points. Secondly, the gradients of each pixel within the 8x8
neighborhood of feature point are calculated. Then the feature point is described by the main direction. After that, the
eigenvector descriptor of the feature point is calculated. Finally, matching is conducted between the feature points of
current frame and reference frame. Compensation of the image is processed after the calculation of global motion vector
from the local motion vector. According to the experimental results, the improved Harris-SIFT algorithm is less complex
than the traditional SIFT algorithm as well as maintaining the same matching precision with faster processing speed. The
algorithm can be applied in real time scenario. More than 80% match time can be saved for every two frames than the
original algorithm. At the same time, the proposed algorithm is still valid when there are slightly rotations between the
two matched frames. It is of important significance in electronic image stabilization technology.