多尺度结构自相似性是指同一幅图像中存在相同尺度或不同尺度的相似结构,这种图像结构自相似性广泛存在于自然图像中。提出了一种基于多尺度结构自相似性的单幅图像超分辨率(Super Resolution,SR)算法,该算法不依赖于外界图像,仅在原始...多尺度结构自相似性是指同一幅图像中存在相同尺度或不同尺度的相似结构,这种图像结构自相似性广泛存在于自然图像中。提出了一种基于多尺度结构自相似性的单幅图像超分辨率(Super Resolution,SR)算法,该算法不依赖于外界图像,仅在原始图像的多尺度图像中搜索低分辨率(Low Resolution,LR)图像块的最相似子块,并结合脊回归算法获得低分辨率图像块和相应高分辨率(High Resolution,HR)图像块的映射关系。此外,将原始图像进行旋转、翻转等操作,扩大内部图像块的样本空间。大量的对比实验表明,本文所提算法有效地提高了峰值信噪比(Peak Signal to Noise Ratio,PSNR)和图像可视效果。展开更多
The performances of repaired image depend on the local information in the repaired area and the consistency between the repair directions with structural content.Image repair algorithm with texture information perform...The performances of repaired image depend on the local information in the repaired area and the consistency between the repair directions with structural content.Image repair algorithm with texture information performs well in repairing seriously damaged images,but it has bad performances when the images have the abundant structure information.The dual optimization image repair algorithm based on the linear structure and the optimal texture is proposed.The algorithm uses the double-constraint sparse model to reconstruct the missed information in large area in order to improve the clarity of repaired images.After adopting the preference of Criminisi priority,the image repair algorithm of self-similarity characteristics is proposed to improve the fault and fuzzy distortion phenomena in the repaired image.The results show that the proposed algorithm has more clarity in the image texture and structure and better effectiveness,and the peak signal-to-noise ratio of the repaired images by proposed algorithm is superior to that by other algorithms.展开更多
文摘多尺度结构自相似性是指同一幅图像中存在相同尺度或不同尺度的相似结构,这种图像结构自相似性广泛存在于自然图像中。提出了一种基于多尺度结构自相似性的单幅图像超分辨率(Super Resolution,SR)算法,该算法不依赖于外界图像,仅在原始图像的多尺度图像中搜索低分辨率(Low Resolution,LR)图像块的最相似子块,并结合脊回归算法获得低分辨率图像块和相应高分辨率(High Resolution,HR)图像块的映射关系。此外,将原始图像进行旋转、翻转等操作,扩大内部图像块的样本空间。大量的对比实验表明,本文所提算法有效地提高了峰值信噪比(Peak Signal to Noise Ratio,PSNR)和图像可视效果。
基金Project(12GJ6055)supported by the Natural Science Foundation of Hunan Province,ChinaProject(2010FJ4107)supported by Hunan Provincial Science and Technology Department,China
文摘The performances of repaired image depend on the local information in the repaired area and the consistency between the repair directions with structural content.Image repair algorithm with texture information performs well in repairing seriously damaged images,but it has bad performances when the images have the abundant structure information.The dual optimization image repair algorithm based on the linear structure and the optimal texture is proposed.The algorithm uses the double-constraint sparse model to reconstruct the missed information in large area in order to improve the clarity of repaired images.After adopting the preference of Criminisi priority,the image repair algorithm of self-similarity characteristics is proposed to improve the fault and fuzzy distortion phenomena in the repaired image.The results show that the proposed algorithm has more clarity in the image texture and structure and better effectiveness,and the peak signal-to-noise ratio of the repaired images by proposed algorithm is superior to that by other algorithms.
