Jian Zhong Cao

Multi-Frame Super-Resolution Reconstruction Algorithm Based on Diffusion Tensor Regularization Term

This paper presents a multi-frame super-resolution (SR) reconstruction algorithm based on diffusion tensor regularization term. Firstly, L1-norm structure is used as data fidelity term, anisotropic diffusion equation with directional smooth characteristics is introduced as a prior knowledge to optimize reconstruction result. Secondly, combined with shock filter, SR reconstruction energy functional is established. Finally, Euler-Lagrange equation based on nonlinear diffusion model is exported. Simulation results validate that the proposed algorithm enhances image edges and suppresses noise effectively, which proves better robustness.

Image denoising algorithm via spatially adaptive bilateral filtering

The classical bilateral filtering algorithm is a non-linear and non-iterative image denoising method in spatial domain which utilizes the spatial information and the intensity information between a point and its neighbors to smooth the noisy images while preserving edges well. To further improve the image denoising performance, a spatially adaptive bilateral filtering image deonoising algorithm with low computational complexity is proposed. The proposed algorithm takes advantage of the local statistics characteristic of the image signal to better preserve the edges or textures while suppressing the noise. Experiment results show that the proposed image denoising algorithm achieves better performance than the classical bilateral filtering image denoising method.

Detail enhancement for high dynamic range images rendering based on multi-level decomposition

Various tone reproduction operators have been proposed to display high dynamic range images on low dynamic range (LDR) devices. Many recent computational photography techniques decompose an image into a piecewise smooth base layer, containing large scale variations in intensity, and a residual detail layer capturing the smaller scale details in the image. In these techniques, its important to control the scale of the extracted details and it is often needed to manipulate details in order to avoid the appearance of visual artifacts. In this paper, a new method is proposed to preserve details for high dynamic range images tone reproduction using multi-level image decomposition. We show that current base-detail decomposition techniques, based on the bilateral filter, are limited in their ability to extract detail at arbitrary scales. Thus, we achieve detail enhancement by applying the bilateral filter iteratively, and this process is called multi-level decomposition. By minimizing the proposed energy function, we can choose the proper decomposition level. Simulation results demonstrate that the proposed method can acquire better visual quality in detail enhancement while make the base smoothness.

An Improved Hough Transform Algorithm Based on Pyramid Method

Hough Transform [ has become a common method in the usage of line detection because of its robustness. It is important in computer vision and image analysis. Usually, the standard Hough transform method (SHT) transform the points in image space into parameter space and vote for all the possible patterns passing through that point. But, there are two serious problems in the standard method of line detection. The first is the high computation complexity and the second is the large storage requirements .In order to solve the two problems, this paper raise a fast-Hough transform algorithm base on pyramid algorithm. First of all we need to desample the primitive binary image with n times; and execute the Hough transform in the nth level image to get the parameter of straight line in this image, which is used in the n-1 level image. Finally we can get the parameter of lines in the primitive image. Experiments show that this method can extremely reduces the computational time.

Mechanical Passive Compensation for Athermalisation Design of Infrared Optical System

Optical equipments especially those for aerospace application are expected to work over a wide temperature range. The change of temperature could cause the refractive index change of infrared glass elements. Furthermore, it would lead to the defocus of the image surface and the performance degradation, so the method of temperature compensation must be adopted, which could make sure that optical system would adapt to the change of ambient temperature. A method of temperature compensation with mechanical passive compensation is briefly described, and an example is also given. The quality of image could be optimized through mechanical passive compensation,depending on the differences of metal and non-metallic thermal expansion coefficient. The results show that the optical system works stablely in the designed temperature range. It is of great importance to the athermalisation design of infrared optical system.

Design of long-wave infrared scan system with rotating dual-wedge prism

Due to the possession of advantages of passivity working mode, good disguise, and easy observation, infrared systems are used in a wide variety of applications. This paper using 640×480 uncooled detector designed a long-wave scan optical system with large field and large aperture working at 8.0μm～12μm, the Pixel Dimensions of the detector is 30μm. The F number of this system is 1.4 and focal length is 17mm, FOV is 63.6°, which extended to 143° by adopting dual-wedge prism rotating, the paper also given the extended field theory by the dual-wedge prism. Because there are a limited number of lens materials used in LWIR spectral bands, Germanium material and three aspheric surfaces were adopted to balance sphere aberrations and chromatic aberration. All above mentioned are intending to ensure the system has good imaging quality. The results show that the optical performance approximates to the diffraction limit and the design has better achromatic performance. The modulation transfer function (MTF) is above 0.5 at spatial frequency of 20lp/mm, energy concentration ratio is greater than 70% within the sensing element of the detector and Root Mean Square (RMS) value of spot diameter is smaller than the Pixel Dimensions. The system has advantages of simple structure, large aperture, high image quality etc.

An Improved Method Based on Fast Bilateral Filter for High Dynamic Image Rendering

This paper presents an improved high dynamic range image tone mapping method based on fast bilateral filtering. The algorithm first applied a bilateral filtering to the luminance channel of the image, the image is decomposed into an HDR base layer and an LDR detail layer. Then the HDR base layer is blurred with bilateral filtering again, get the details portion of the base layer, at the same time the dynamic range of the global base layer is compressed. Finally, the detail component and the compressed HDR base layer are recombined and the result is tone-mapped image for displaying. For color image, the color restoration converts luminance value into RGB color. Experimental results show that the proposed technique performed better than the conventional bilateral filtering, preserving more details and enhancing local contrast, giving decent visual effect and avoiding additional artifacts.

The Design of a Hybrid Diffractive-Refractive Wide-Angle Eyepiece with a Large Exit Pupil Distance

The diffractive optical elements, with the negative dispersive characteristic and the random phase distributing to realize random phase modulation for wave-front, are not only helpful to simplify the optical system, but also improve the image quality, while putting it into the optical system. It can decrease the element numbers of the system and obtain a compact configuration that introducing diffractive optical element into the design of eyepiece. A hybrid diffractive-refractive wide-angle eyepiece, with a big exit pupil distance, is designed by using the Code V Optical Design Software. The features of the wide-angle eyepiece are 30mm effective focal length, 60°whole field-of-view (FOV), 30mm exit pupil distance and 6mm exit pupil diameter, and which consists of four lens and two diffractive elements. From the result of design, the MTF in the center field of the wide-angle eyepiece is over 0.55at 60lp/mm, at the same time, the MTFs in all fields are over 0.3 at 50lp/mm, which show that this wide-angle eyepiece has a great image quality.

A new super-resolution reconstruction algorithm based on block sparse representation

In this paper, we propose a new single super-resolution (SR) reconstruction algorithm via block sparse representation and regularization constraint. Firstly, discrete K-L transform is used to learn compression sub-dictionary according to the specific image block. Combined with threshold choice of training data, the transform bases are generated adaptively corresponding to the sparse domain. Secondly, Non-local Self-similarity (NLSS) regularization term is introduced into sparse reconstruction objective function as a prior knowledge to optimize reconstruction result. Simulation results validate that the proposed algorithm achieves much better results in PSNR and SSIM. It can both enhance edge and suppress noise effectively, which proves better robustness.

A Joint Method Based on Wavelet and Curvelet Transform for Image Denoising

Wavelet transform is widely used and has good effect on image denoising. Wavelet transform has unique advantages in dealing with the smooth area of image but is not so perfect in high frequency areas such as the edges. However, curvelet transform can supply this gap when dealing with the high frequency areas because of the characteristic of anisotropy. In this paper, we proposed a new method which is based on the combination of wavelet transform and curvelet transform. Firstly, we detected the edges of the noisy-image using wavelet transform. Based on the edges we divided the image into two parts: the smoothness and the edges. Then, we used different transform methods to dispose different areas of the image, wavelet threshold denoising is used in smoothness while FDCT denoising is used in edges. Experimental results showed that we could get better visual effect and higher PSNR, which indicated that the proposed method is better than using wavelet transform or curvelet transform respectively.