Edge Pattern Based Demosaicking Algorithm of Color Filter Array

An efficient adaptive approximation demosaicking algorithm based on the sampled edge pattern was presented for mosaic images from Bayer color filter array. The proposed algorithm determined edge patterns by four nearest green values surrounding the green interpolation location. Then according to the edge patterns, different adaptive interpolation steps were applied. Simulations on 12 Kodak photos and 15 IMAX high-quality images showed that the proposed method outperformed the other four demosaicking methods (bilinear, effective color interpolation, Lu's method and Chen's method) for average color peak signal to noise ratios and maintained a relatively low complexity owing to constant color-difference interpolation step and a reasonable terminating condition of iteration.

Ultralow cross talk arrayed waveguide grating integrated with tunable microring filter array

The silicon-based arrayed waveguide grating(AWG)is widely used due to its compact footprint and its compatibility with the mature CMOS process.However,except for AWGs with ridged waveguides of a few micrometers of cross section,any small process error will cause a large phase deviation in other AWGs,resulting in an increasing cross talk.In this paper,an ultralow cross talk AWG via a tunable microring resonator(MRR)filter is demonstrated on the SOI platform.The measured insertion loss and minimum adjacent cross talk of the designed AWG are approximately 3.2 and-45.1 d B,respectively.Compared with conventional AWG,its cross talk is greatly reduced.

AN ADAPTIVE COLOR PLANE INTERPOLATION METHOD BASED ON EDGE DETECTION

In this letter, an adaptive interpolation algorithm based on edge detection is proposed. With this algorithm, all the missing green values can be reconstructed in Bayer pattern image by using edge detection interpolation method. Reconstructed images composed of green pixels are classified according to the high frequency components in image, and the threshold T needed for all kinds of green images in the edge detection is determined through experiments. The edge detection is carried out based on the one Dimensional (1D) gradient operator. If the gradient value is greater than T, this pixel is located on the edge; otherwise the pixel is in the smooth area of the image. Finally, the simple bilinear interpolation is used for the smooth area while the Laplacian interpolation with the second-order correction term is adopted to reconstruct the other red/blue values on the edge. This algorithm resolves effectively the conflicts between reconstructing high quality color image and reducing computational complexity, and thus largely enhances the processing speed for the reconstructed color image.

Towed line array sonar platform noise suppression based on spatial matrix filtering technology

The spatial matrix filter was designed and used for solving the problem to detect a weak target who was influenced by the strong nearby platform noise interference of the towed line array sonar. The MFP technology and the DOA estimation technology were combined together by using the sound propagation characteristics of both target and interference. The spatial matrix filter with platform noise zero response constraint was designed by the near-field platform noise normal modes copy vectors and the far-field plane wave bearing vectors together. The optimal solution of the optimization problem for designing the spatial matrix filter was deduced directly, and it was simplified by the generalized singular value decomposition. The total response error to the plane wave bearing vectors and the total response to the platform noise copy vectors were given. The phenomena that strong interferences existed in the bearing course and blind areas existed after filtering were analyzed by the correlation between the plat- form noise copy vectors and the plane wave bearing vectors. It could be found from simulations that it has less blind area and higher detection ability by using the spatial matrix filtering technology.

Color reproduction for noisy CFA data using directional cycle-spinning

This paper addresses color filter array（CFA） color reproduction problem where the aim is to utilize an image captured by the CFA to produce an image with full color information.First,conventional subband synthesis based color reproduction techniques do not consider the noise during image acquisition and assume that the CFA data are noiseless.To tackle the noisy CFA data,a novel approach is proposed by inserting a subband denoising scheme into the conventional subband synthesis framework.Second,conventional subband synthesis based techniques exploit the decimated wavelet transform that is not shift-invariant and could result in ringing artifacts in the result.To alleviate these artifacts,the directional cycle-spinning（DCS） technique is exploited.Furthermore,a new cycle-spinning pattern is proposed according to the sampling pattern of the Bayer CFA data.Extensive experiments are conducted to demonstrate that the proposed approach outperforms several approaches.

Experimental realization of a switchable filter based on a dynamically transformable array

We introduce a geometrically reconfigurable metasurface whose artificial ＂atoms＂ will reorient within unit ceils in response to a thermal stimulus in the microwave spectrum. It can alternate between two contrasting behaviors under different temperatures and serve as a switchable filter that allows the incident energy to be selectively transmitted or reflected with an excess of 10 dB isolation at certain frequencies for both polarizations. The ex- perimental results are consistent with the theoretical simulations, verifying the availability of an innovative method for manipulating electromagnetic waves with the merits of higher controllability for dynamic behavior and greater flexibility in the design process.

Hybrid fusion and interpolation algorithm with near-infrared image

Silicon-based digital cameras can record visible and near-infrared （NIR） information, in which the full color visible image （RGB） must be restored from color filter ar- ray （CFA） interpolation. In this paper, we propose a uni- fied framework for CFA interpolation and visible/NIR image combination. To obtain a high quality color image, the tra- ditional color interpolation from raw CFA data is improved at each pixel, which is constrained by the corresponding monochromatic NIR image in gradient difference. The ex- periments indicate the effectiveness of this hybrid scheme to acquire joint color and NIR information in real-time, and show that this hybrid process can generate a better color im- age when compared to treating interpolation and fusion sep- arately.

A Low Complexity and High Efficient Method for Image Compression with Bayer CFAs

This paper presents a novel method of Iossy image compression for digital colorful image sensors with Bayer color filter arrays （CFAs） based on an analysis of existing compression-first methods. An improved compression and decompression structure is described. The captured CFA raw data are firstly lowpass filtered in RGB space by a smooth filter followed by a down-sampling operation. Next, the data are transformed from RGB space to YCbCr space. Lastly, the filtered data in YCbCr space are compressed directly before full color interpolation to avoid redundancy. The presented method can provide a lower compression ratio and has lower complexity than both conventional interpolation-first image compression methods and other similar existing compression-first methods.