The max/min filters are the most basic operator in gray-scale morphology. van Herk proposed an efficient O(1) rectangular kernel max/min filters algorithm which is independent of the size of filter window. This paper mainly studies the parallel optimization of van Herk’s max/min filters algorithm by using the single-instruction, multiple data (SIMD) technology and OpenMP parallel optimization technology for multi-core processors. First, the Intel Sreaming SIMD Extensions 2 (SSE2) is used to perform data-level parallel optimization for van Herk’s max/min filters algorithm in column direction, and a method based on histogram statistics is proposed to accelerate the calculation in row direction, the parallel speed-up ratio can reach 2. Then, the OpenMP parallel optimization technology is used to further perform thread-level parallel optimization for the SSE2 optimized version. The total speedup ratio under 4 cores and 4 threads CPU is about 7. Finally, compared with the rectangular kernel gray morphological operators in the powerful machine vision software MVTec HALCON17.12, the optimized algorithm in this paper has a great advantage in large window filtering size.
Distance measure of point to segment is one of the determinants which affect the efficiency of DP (Douglas-Peucker)
polyline simplification algorithm. Zone-divided distance measure instead of only perpendicular distance is proposed by
Dan Sunday  to improve the deficiency of the original DP algorithm. A new efficiency zone-divided distance measure
method is proposed in this paper. Firstly, a rotating coordinate is established based on the two endpoints of curve.
Secondly, the new coordinate value in the rotating coordinate is computed for each point. Finally, the new coordinate
values are used to divide points into three zones and to calculate distance, Manhattan distance is adopted in zone I and
III, perpendicular distance in zone II. Compared with Dan Sunday’s method, the proposed method can take full
advantage of the computation result of previous point. The calculation amount basically keeps for points in zone I and
III, and the calculation amount reduces significantly for points in zone II which own highest proportion. Experimental
results show that the proposed distance measure method can improve the efficiency of original DP algorithm.
This paper introduces a coaxial visible and infrared dual-band imager, which utilizes the visible and infrared detection technology, uptakes the scenery radiation of different wavelengths or optical energy reflected, adopts transmission and secondary reflection theory to design the coaxial optical path, and realizes the dual-band imaging of same scene. The imager can acquire the registered visible and infrared images, and effectively solves the problem of registration for visible and infrared images in different-source image fusion.
Image fusion is a process of combing multiple images of the same scene into a single image with the aim to preserve the
full content information and retain the important features from each of the combined images. In this paper, a novel image
fusion method based on Wavelet Transform (WT) and Visual Attention Mechanism (VAM) is proposed. Firstly, the
source images are decomposed by WT to get the sub-images. Secondly, by using the VAM, the salience maps of the
source images are formed, which can indicate the salient regions to the human visual system, i.e., the higher the saliency
value is, the more important the location represent. The saliency maps are then used together with the match measure
between the coefficients to guide the combination of the coefficients as follows: if the match measure at a given location
is low, the coefficient from the source image with higher saliency is selected to be the fused coefficient. Contrarily, if the
match measure at a given location is high, then the fused coefficients are calculated as the weighted sum of the
coefficients extracted from both source images. The weights here are determined by the corresponding saliency maps of
the source images. Finally, the fusion image is obtained by using the inverse WT transform. Experimental results
applying the proposed algorithm show that the fused image keeps more visual meaningful information than other