计算机科学 ›› 2020, Vol. 47 ›› Issue (4): 131-135.doi: 10.11896/jsjkx.190300149
周先春1,2, 徐燕1
ZHOU Xian-chun1,2, XU Yan1
摘要： 针对传统的Criminisi修复算法中优先函数计算的不足,以及修复后图像质量下降的问题,文中提出了一种基于结构相关性的自适应图像修复算法。首先,引入结构相关性,对优先权计算进行改进,增加优先权计算的可靠性;然后,自适应选择样本块大小,使修复更加准确并提高修复效率;最后,引入HSV颜色空间,根据样本的色度、亮度来搜寻最佳匹配块,减少修复误差,完成图像恢复。实验结果表明,所提算法在主观视觉上有明显提升,并且在峰值信噪比(PSNR)和结构相似度(SSIM)方面均有一定提高,修复效果明显,与传统的Criminisi修复算法相比,其峰值信噪比提高了1～3dB,结构相似度更接近1。所提算法利用结构相关性和自适应选择样本块大小对彩色破损图像进行修复,优先权计算更加合理准确,修复效率有所提高,修复效果可视性更佳,有利于实际应用。
中图分类号:
| [1]GUILLEMOT C,LE M O.Image inpainting:overview and recent advances[J].IEEE Signal Processing Magazine,2014,31(1):127-144. [2]ZHANG H Y,PENG Q Z.Overview of digital image restoration technology[J].Journal of Image and Graphics,2007,12(1):1-10. [3]BERTALMIO M,SAPIRO G,CASELLES V,et al.Image inpainting[J].Proceedings of Siggraph,2000,4(19):417-424. [4]YU L J,JING,LI Y W.Double Cross Algorithm of Improved TV Image Inpainting Model [J].IEEE 3rd Advanced Information Technology,Electronic and Automation Control Confe-rence,2018,7(5):1097-1100. [5]CHEN Q C,LI G Y,LI X,et al.Structure guided image completion using texture synthesis and region segmentation[J].Optik,2019,6(4):896-909. [6]ZHOU X C,WANG M L,SHI L F.Research on image smoothing model based on the combination of gradient and curvature[J].Acta Physica Sinica,2015,64(4):1-7. [7]LIU Z X,WAN W G.Image Inpainting Algorithm Based on KSVD and Improved CDD[C]// Conference on International Conference on Audio,Language and Image Processing (ICALIP).Shanghai:2018:413-417. [8]ZHOU X C,WANG M L,ZHOU L F.The image of quasi-normal distribution diffusion is smooth[J].Journal of Image and Graphics,2015,20(2):169-176. [9]CRIMINISI A,PEREZ P,TOYAMA K.Region filling and object removal by exemplar-based image inpainting[J].IEEE Transactions on Image Processing,2004,13(9):1200-1212. [10]ZHOU Y T,LI L.Research on weighted priority of exemplarbased image inpainting[J].Journal of Electronics,2012,29(1):166-170. [11]LI A J,NIU W L.Image inpainting based on improved Criminisi algorithm[J].Computer Engineering and Applications,2014,50(18):167-170. [12]WANG S M.An unidirectional Criminisi Algorithm for DIBR-synthesized images[C]// 2nd IEEE International Conference on Computer and Communications (ICCC).Chengdu:2016:574-578. [13]HE K M,SUN J.Image completion approaches using the statistics of similar patches[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2014,36(12):2423-2435. [14]HUANG Y,LI K,YANG M.An Improved Image InpaintingAlgorithm Based on Image Segmentation[J].Procedia Compu-ter Science,2017,107(3):796-801. [15]ZHI H C,CHAO D,LEI J,et al.Structure-aware image inpainting using patch scale optimization[J].Journal of Visual Communication and Image Representation,2016,40(1):312-323. [16]WANG P Y,ZHAO D H,LI M F.Target visible light camouflage effect evaluation based on image inpainting technology[J].Advances in laser and optoelectronics,2018,55(3):31011. [17]ZHANG Q H,SHI P F.Edge extraction method based on HSV space color image[J].Computer Simulation,2000,11(17):25-32. [18]SIADAT S Z,YAGHMAEE F,MAHDAV P.A new exemplar-based image inpainting algorithm using image structure tensors[C]//Proceeding of the 24th Iranian Conference on Electrical Engineering.Shiraz,Iran:IEEE,2016:995-1001. [19]DOU L Y,XU D,LI J,et al.Image inpainting based on double tree complex wavelet[J].Computer Science,2017,44(1):179-182,191. |
| [1] | 赵露露, 沈玲, 洪日昌. 图像修复研究进展综述 Survey on Image Inpainting Research Progress 计算机科学, 2021, 48(3): 14-26. https://doi.org/10.11896/jsjkx.210100048 |
| [2] | 刘浪, 李梁, 但远宏. 用于视频修复的连贯语义时空注意力网络 Coherent Semantic Spatial-Temporal Attention Network for Video Inpainting 计算机科学, 2021, 48(10): 239-245. https://doi.org/10.11896/jsjkx.200600130 |
| [3] | 孟丽莎, 任坤, 范春奇, 黄泷. 基于密集卷积生成对抗网络的图像修复 Dense Convolution Generative Adversarial Networks Based Image Inpainting 计算机科学, 2020, 47(8): 202-207. https://doi.org/10.11896/jsjkx.190700017 |
| [4] | 王晓, 邹泽伟, 李勃勃, 王静. 基于多特征融合的彩色图像声呐目标检测 Target Detection in Colorful Imaging Sonar Based on Multi-feature Fusion 计算机科学, 2019, 46(6A): 177-181. |
| [5] | 甘玲, 赵福超, 杨梦. 一种自适应组稀疏表示的图像修复方法 Self-adaptive Group Sparse Representation Method for Image Inpainting 计算机科学, 2018, 45(8): 272-276. https://doi.org/10.11896/j.issn.1002-137X.2018.08.049 |
| [6] | 张雷,康宝生. 基于结构稀疏度和块差异度的目标移除图像修复 Image Inpainting for Object Removal Based on Structure Sparsity and Patch Difference 计算机科学, 2018, 45(5): 255-259. https://doi.org/10.11896/j.issn.1002-137X.2018.05.044 |
| [7] | 孙全, 曾晓勤. 基于生成对抗网络的图像修复 Image Inpainting Based on Generative Adversarial Networks 计算机科学, 2018, 45(12): 229-234. https://doi.org/10.11896／j.issn.1002-137X.2018.12.038 |
| [8] | 胡志军, 刘广海, 苏又. 局部自相关函数在基于内容的图像检索中的应用 Application of Local Autocorrelation Function in Content-based Image Retrieval 计算机科学, 2018, 45(11A): 259-262. |
| [9] | 窦立云,徐丹,李杰,陈浩,刘义成. 基于双树复小波的图像修复 Image Inpainting Based on Dual-tree Complex Wavelet Transform 计算机科学, 2017, 44(Z6): 179-182. https://doi.org/10.11896/j.issn.1002-137X.2017.6A.041 |
| [10] | 祝轩,张旭峰,李秋菊,王宁,陶吉瑶. 基于稀疏分解的图像修复方法 Image Inpainting Method Based on Sparse Decomposition 计算机科学, 2016, 43(1): 294-297. https://doi.org/10.11896/j.issn.1002-137X.2016.01.063 |
| [11] | 睢 丹,高国伟. 基于人工鱼群微细分解的先验未知像素点修复算法 Image Restoration Algorithm of Unknown Priori Pixel Based on Artificial Fish Swarm Decomposition 计算机科学, 2015, 42(3): 316-320. https://doi.org/10.11896/j.issn.1002-137X.2015.03.065 |
| [12] | 胡文瑾,刘仲民,李战明. 一种改进的小波域图像修复算法 Improved Algorithm for Image Inpainting in Wavelet Domains 计算机科学, 2014, 41(5): 299-303. https://doi.org/10.11896/j.issn.1002-137X.2014.05.064 |
| [13] | 翟东海,李同亮,段维夏,鱼江,肖杰. 基于矩阵相似度的最佳样本块匹配算法及其在图像修复中的应用 Optimal Exemplar Matching Algorithm Based on Matrix Similarity and its Application in Image Inpainting 计算机科学, 2014, 41(1): 307-310. |
| [14] | 刘纯利,张弓. 基于小波框架的盲图像修复研究 Wavelet Frame Based Blind Image Inpainting 计算机科学, 2013, 40(4): 295-297. |
| [15] | 刘广海,吴璟莉. 基于颜色体积直方图的图像检索 Image Retrieval Based on Color Volume Histogram 计算机科学, 2012, 39(1): 273-275. |
|
||
首页