Bi-Directional Filter for the Removal of Lines and Cracks in Images

In this paper, a method for the removal of noisy lines and cracks corrupted by different noise types is explored, using a cascade of filtering cycles based on the principle of symmetry among neighboring pixels. Each filtering cycle includes a filter in two perpendicular directions, one horizontal and the other vertical. Any pixel, to be deemed original, should have a number of symmetric pixels within its neighboring pixels greater than the number specified by the condition set for each direction in all the filters. Since the conditions of each filter increase gradually from one cycle to the next, it becomes more difficult for a noisy pixel to satisfy the filter conditions in each filtering cycle, while an original pixel can easily satisfy the conditions in all the filtering cycles. The reason is that a noisy pixel has a random value and therefore faces difficulty in finding a sufficient number of symmetric pixels in each direction, while an original one has a value correlated with the values of its neighboring pixels. Extensive simulation experiments prove that the proposed method efficiently detects and restores different noisy lines and cracks of different shape and thickness. Also, it retains the image details and outperforms other well-known algorithms, both objectively and subjectively. More specifically, the proposed algorithm achieves restoration performance better than the other known methods by ≥0.81dB in all simulation experiments.

An Image Fusion Algorithm based on Modified Contourlet Transform

Multi-focus image fusion has established itself as a useful tool for reducing the amount of raw data and it aims at overcoming imaging cameras’ finite depth of f ield by combining information from multiple images with the same scene. Most of existing fusion algorithms use the method of multi-scale decompositions (MSD) to fuse the s ource images. MSD-based fusion algorithms provide much better performance than the conventional fusion methods .In the image fusion algorithm based on multi-scale decomposition, how to make full use of the characteristics of coefficients to fuse images is a key problem.This paper proposed a modified contourlet transform(MCT) based on wavelets and nonsubsampled directional filter banks(NSDFB). The image is decomposed in wavelet domain,and each highpass subband of wavelets is further decomposed into multiple directional subbands by using NSDFB. The MCT has the important features of directionality and translation invariance. Furthermore, the MCT and a novel region energy strategy are exploited to perform image fusion algorithm. simulation results shows that the proposed method can the fusion results visually and also improve in objective evaluating parameters.

Compact SIW directional filter using substrate integrated circular cavities

In this paper, a novel directional filter (DF) is proposed and implemented using substrate integrated waveguide (SIW) technology which exhibits the advantages of compact size and simple structure. The proposed DF is realized by two half mode substrate integrated waveguides (HMSIWs) and two substrate integrated circular cavity (SICC) resonators operating in the TM110 degenerate modes in which an aperture is utilized to realize the coupling between HMSIWs and SICCs. Two slotlines with appropriate dimensions, etched on the top and bottom planes, are utilized in order to control coupling strength between two cascaded SICC resonators. The proposed two-circular cavity SIW DF at 12.3 GHz is designed and fabricated with a normal printed circuit board process. Measured and simulated results indicate that the DF has a 3.25% bandwidth, and the return loss as well as isolation are better than 10.5 and 15 dB, respectively.