应用图像分层法和偏微分方程的数字图像修复
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摘要
图像由于各种原因被损坏或变得残缺不全。本文研究用Inpainting技术进行图像修复。图像修复是模仿古代画家对绘画的手工修复,用计算机及专门算法对图像进行润饰,达到修复效果。这项工作无法用传统的图像恢复、重建、增强来完成。
我们对图像修复进行深入的探讨,提出了以下新方法。
1.提出一种方法用于改善在不理想天气条件下拍摄的照片质量。通过阈值分割获得照片中包含天空部分的模板,然后使用另一幅图像中的蓝色天空来代替待改善照片中的灰暗天空。由于在天空和地面物体之间的复杂边界没有明确定义,因而我们引入纹理生长方法,在边界处生成新的纹理,使得修饰后的图像视觉上更加自然。
2.提出一种基于图像分层的图像修复算法。首先利用DCT将待修复的图像分解成三层:结构层(Cartoon)、边缘层、纹理层。对结构层和边缘层中的损坏区域使用自适应偏心平滑算子进行修复,避免使边缘区域产生模糊;对纹理层中的损坏区域使用纹理合成法进行修复。与一些已报道的方法相比,提出的方法能够产生较好的修复效果,并且具有较快的处理速度。
3.利用热传导模型解决图像修复问题,在该模型中像素灰度值等价于热传导中的温度。采用有限差分法来数值求解偏微分方程,待修复区域的邻域信息通过不断迭代的方式传播至损伤区域。在用迭代法求解PDE时分别采用1个像素和2个像素两种不同的空间步长,步长较小时给出了更好的修复效果。该方法与其它PDE方法相比相对简单,并对Cartoon层能取得满意的修复效果。纹理信息从损伤域的周围提取得到,并叠加至修复区以产生更自然的效果。
我们对各种图像在不同类型损伤的条件下进行了大量的实验,结果表明上述方法具有良好的处理效果。
Images can be degraded,damaged,and even vandalized.This work deals with the problems of repairing damaged images using a technique called "image inpainting" since traditional image restoration,reconstruction,and enhancement can hardly be used to deal with some of the problems.Image inpainting is to use computer and specialized algorithms to automatically do the job of picture retouching that would have been done manually by an art professional in the old days.
In recent years,many techniques for image inpainting have been developed and applied for various applications such as removing scratches,defects,super-imposed text,or even entire object from the scene in an undetectable manner.However,as it is a new field of research,many problems remain unsolved,therefore extensive investigations are needed to advance the research and make the techniques practical.
In this work,we propose several new methods in order to contribute to the development of this attractive and useful area in image processing.
First,we propose a method to improve quality of photographs taken under poor weather conditions.We use a thresholding operation to segment the image to obtain a template for the sky.The gloomy sky is replaced with a patch,which is cloned from an available picture of blue sky,using an algebraic operation.For the fine retouch of complicated boundaries where transition between the sky and ground objects is not clearly defined,a texture growing method is introduced to generate the texture along the boundary.This makes the modified image look natural.
Second,we develop a layered image inpainting method.The damaged image is first decomposed into three layers:cartoon,edge,and texture using DCT.The cartoon and edge layers are repaired using an adaptive offset operator that can fill-in damaged image blocks while preserving sharpness of edges.The missing information in the texture layer is generated with a texture synthesis method.Compared with some existing techniques,the proposed method can produce good image with less blurring of the edges and a faster processing speed.
Third,we use a heat transfer model to solve the problem of image inpainting,in which the pixel gray level is made analogous to temperature.A finite difference method is developed to solve the partial differential equations(PDE) numerically,using double-grid and single-grid iteration schemes.Information contained in the neighborhood is propagated into the missing area progressively.This method is relatively simple as compared to other PDE approaches,and gives satisfactory fill-in effects of the cartoon layer of the damaged image.Texture information is extracted from the area around the hole,and added to the repaired patches to produce a more natural appearance.
Experiments have been carded out on images with various types of damages to show the effectiveness of the proposed methods.
我们对图像修复进行深入的探讨,提出了以下新方法。
1.提出一种方法用于改善在不理想天气条件下拍摄的照片质量。通过阈值分割获得照片中包含天空部分的模板,然后使用另一幅图像中的蓝色天空来代替待改善照片中的灰暗天空。由于在天空和地面物体之间的复杂边界没有明确定义,因而我们引入纹理生长方法,在边界处生成新的纹理,使得修饰后的图像视觉上更加自然。
2.提出一种基于图像分层的图像修复算法。首先利用DCT将待修复的图像分解成三层:结构层(Cartoon)、边缘层、纹理层。对结构层和边缘层中的损坏区域使用自适应偏心平滑算子进行修复,避免使边缘区域产生模糊;对纹理层中的损坏区域使用纹理合成法进行修复。与一些已报道的方法相比,提出的方法能够产生较好的修复效果,并且具有较快的处理速度。
3.利用热传导模型解决图像修复问题,在该模型中像素灰度值等价于热传导中的温度。采用有限差分法来数值求解偏微分方程,待修复区域的邻域信息通过不断迭代的方式传播至损伤区域。在用迭代法求解PDE时分别采用1个像素和2个像素两种不同的空间步长,步长较小时给出了更好的修复效果。该方法与其它PDE方法相比相对简单,并对Cartoon层能取得满意的修复效果。纹理信息从损伤域的周围提取得到,并叠加至修复区以产生更自然的效果。
我们对各种图像在不同类型损伤的条件下进行了大量的实验,结果表明上述方法具有良好的处理效果。
Images can be degraded,damaged,and even vandalized.This work deals with the problems of repairing damaged images using a technique called "image inpainting" since traditional image restoration,reconstruction,and enhancement can hardly be used to deal with some of the problems.Image inpainting is to use computer and specialized algorithms to automatically do the job of picture retouching that would have been done manually by an art professional in the old days.
In recent years,many techniques for image inpainting have been developed and applied for various applications such as removing scratches,defects,super-imposed text,or even entire object from the scene in an undetectable manner.However,as it is a new field of research,many problems remain unsolved,therefore extensive investigations are needed to advance the research and make the techniques practical.
In this work,we propose several new methods in order to contribute to the development of this attractive and useful area in image processing.
First,we propose a method to improve quality of photographs taken under poor weather conditions.We use a thresholding operation to segment the image to obtain a template for the sky.The gloomy sky is replaced with a patch,which is cloned from an available picture of blue sky,using an algebraic operation.For the fine retouch of complicated boundaries where transition between the sky and ground objects is not clearly defined,a texture growing method is introduced to generate the texture along the boundary.This makes the modified image look natural.
Second,we develop a layered image inpainting method.The damaged image is first decomposed into three layers:cartoon,edge,and texture using DCT.The cartoon and edge layers are repaired using an adaptive offset operator that can fill-in damaged image blocks while preserving sharpness of edges.The missing information in the texture layer is generated with a texture synthesis method.Compared with some existing techniques,the proposed method can produce good image with less blurring of the edges and a faster processing speed.
Third,we use a heat transfer model to solve the problem of image inpainting,in which the pixel gray level is made analogous to temperature.A finite difference method is developed to solve the partial differential equations(PDE) numerically,using double-grid and single-grid iteration schemes.Information contained in the neighborhood is propagated into the missing area progressively.This method is relatively simple as compared to other PDE approaches,and gives satisfactory fill-in effects of the cartoon layer of the damaged image.Texture information is extracted from the area around the hole,and added to the repaired patches to produce a more natural appearance.
Experiments have been carded out on images with various types of damages to show the effectiveness of the proposed methods.
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