Because the infrared images have the disadvantage of low contrast and fuzzy edges, it is not suitable for us to observe them, so it is necessary to first make enhanced processing before recognition. Though the existing enhancement methods do not take into account the characteristics of HVS, the visual effect of the processed images is not good. Therefore, the paper proposes an enhancement algorithm of infrared images that combine multi-resolution wavelet transform with Retinex theory, it blends with the characteristics of HVS in order to make high-frequency details of infrared images strengthen and illumination uniformity strength and the brightness of IR images moderate. Through experimental results and data analysis, it not only improves the infrared images of low contrast and fuzzy detail, but also suppresses the noise in images to strengthen the overall visual effect of the infrared images.
Based on the scene characteristics of frequency distribution in the degraded color images, the MSRCR method and wavelet transform in the paper are introduced respectively to enhance color images and the advantages and disadvantages of them are analyzed combining with the experiment, then the combination of improved MSRCR method and wavelet transform are proposed to enhance color images, it uses wavelet to decompose color images in order to increase the coefficient of low-level details and reduce top-level details to highlight the scene information, meanwhile, the method of improved MSRCR is used to enhance the low-frequency components of degraded images processed by wavelet, then the adaptive equalization is carried on to further enhance images, finally, the enhanced color images are acquired with the reconstruction of all the coefficients brought by the wavelet transform. Through the evaluation of the experimental results and data analysis, it shows that the method proposed in the paper is better than the separate use of wavelet transform and MSRCR method.
Due to inclement weather caused frequently, such as clouds, fog , rain etc. The light intensity on the illuminated objects falls sharply, it make the scenes captured unclear, poor visual quality and low contrast degree. To improve the overall quality of these images, especially the bad illuminated images, the paper propose a new color image enhancement algorithm which is based on multi-scale Retinex theory with color recovering factor (MSRCR) and the human visual system (HVS). It can effectively solve the problem of the color balance of digital images by removing the influence of light and obtain component images reflected the reflex of the object surface, meanwhile, reduce the impact of non-artificial factors and overcome the Ringing effect and human interference. Through comparison and contrast among experiments, that combined evaluated parameters on enhancement image, such as variance, average gradient, sharpness and so forth with the traditional image enhancement methods, such as histogram enhancement, adaptive histogram enhancement, the MSRCR algorithm is proved to be effective in image contrast, detail enhancement and color fidelity, etc.