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xiuzi0731銀蟲 (小有名氣)
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[求助]
求助翻譯一段摘要
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| 針對(duì)細(xì)胞圖像序列模糊,傳統(tǒng)的特征提取方法魯棒性不強(qiáng),偽匹配點(diǎn)對(duì)較多,圖像匹配耗時(shí)過(guò)長(zhǎng),融合效果不佳等問(wèn)題,提出了一種強(qiáng)魯棒性、快速和精確的圖像拼接算法。該算法首先用基于尺度不變(SIFT)算法提取細(xì)胞圖像特征點(diǎn);接著采用改進(jìn)的BBF(Best-Bin-First)算法對(duì)特征集進(jìn)行初始的雙向匹配;然后采用隨機(jī)抽樣一致性(RANSAC)算法對(duì)匹配點(diǎn)對(duì)進(jìn)行進(jìn)一步提純并估算出單應(yīng)性矩陣;最后根據(jù)細(xì)胞圖像序列之間的單應(yīng)性矩陣關(guān)系,將其投影到統(tǒng)一標(biāo)準(zhǔn)的平面坐標(biāo)系下,用具有塔型結(jié)構(gòu)的多分辨率融合算法對(duì)圖像進(jìn)行無(wú)縫融合,完成全景圖拼接。實(shí)驗(yàn)結(jié)果證明:該算法提取到的提取到的特征點(diǎn)分布均勻且數(shù)量適中,誤配情況明顯減少,能夠有效地實(shí)現(xiàn)顯微全景圖的無(wú)縫拼接。 |
銀蟲 (小有名氣)
至尊木蟲 (職業(yè)作家)
| For the blurred cell image sequence , the traditional robust feature which is extracted is not evident, pseudo matching points more, image matching takes too long, the effect of poor integration and other issues, presents a strong robust, fast and accurate the image stitching algorithm. The algorithm is based on first with scale-invariant (SIFT) algorithm for image feature points extracted from the cells; then using the improved BBF (Best-Bin-First) algorithm features a two-way matching initial set; then use random sampling consistency (RANSAC) algorithm matching point for further purification and estimate the homography; Finally, according homography relationship between image sequences cells, down to its projection plane coordinate system of uniform standards, with a tower-type structure with multi-resolution seamless fusion algorithm for image fusion, complete panorama stitching. Experimental results show that: the algorithm to extract the feature points extracted to moderate amount evenly distributed and significantly reduce the mismatch situation, can effectively achieve seamless microscopic panorama. |
銀蟲 (小有名氣)
版主 (文壇精英)
| To overcome the problem of cell image sequence blur, bad robust of the traditional extraction method,too much pseudo matching points,long time of the image matching, bad effect of integration,etc.;we presented a good robust ,quick ,and accurate image stitching algorithm. The presented algorithm is based on,firstly,scale-invariant (SIFT) algorithm to extract featured points of the cell image and improved BBF (Best-Bin-First) algorithm to initially set a two-way matching of the featured set. Then,the matching point was further purified and homography estimated by the use of random sampling consistency (RANSAC) algorithm .Finally,the homography relationship of the cell image sequences was projected to standardized plane coordinate system for seamless fusion of the image through a tower- typed structure fusion algorithm of multi-resolution to complete panorama stitching. Results showed that moderate amount extracted feature points were evenly distributed,mismatches were reduced,and the algorithm can realize seamless fusion of microscopic panorama effectively. |

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