图像放大算法的研究
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摘要
如今,数字图像已经在工程和数学领域引起广泛关注,而图像插值技术也已被广泛应用于数字图像处理,例如图像缩放、图像变形、图像恢复、图像重建、图像配准等。
图像插值就是利用已知邻近像素点的灰度值来产生未知像素点的灰度值,以便由原始图像再生出具有更高分辨率的图像。
本文首先通过分析实际图像获取系统将图像数字化后,建立图像的模型,并给出了图像的表示方法,根据数字图像的特点阐述了图像放大的基本原理。
其次,本文介绍了传统的线性移不变插值算法。主要介绍了最近邻插值、线性插值、三次卷积插值、多项式插值、样条插值和高斯插值等。通过对传统的线性移不变图像插值算法的分析,归纳了线性移不变图像插值的共同技术缺陷和它们的理论成因。然后,论文从线性空不变图像插值和距离加偏差图像插值两方面介绍了现代自适应图像插值技术,讨论了各算法的优势和局限性。
自适应插值技术的插值效果比线性移不变插值技术有了较大的改善,但算法复杂计算量大,在实际图像处理系统中应用困难。本文提出了一种基于图像边缘信息的自适应图像插值算法。根据边缘部分映射点邻域图像的复杂程度,自适应地调节插值权值的图像插值方法。应用该算法插值后的边界清晰、自然,忠实地反映了原始图像的面貌,与传统的插值算法相比,其边界处理效果好且易于实现,实验也验证了该方法的有效性。
Today, the digital image in the field of engineering and mathematics has aroused widespread concern, and the image interpolation technology has been widely used in digital image processing, such as image zoom, image deformation, image restoration, image reconstruction.
Image Interpolation is known to use the adjacent pixels to generate unknown gray value of the gray pixels value to the original image from renewable to a higher-resolution images.
In this paper, through analysis of the actual image acquisition system will be digital image after image of the established model, and gives the image of that method, in accordance with the characteristics of digital images on the image to enlarge the basic principles.
Secondly, this paper, the traditional linear interpolation algorithm shift unchanged. Mainly on the nearest neighbor interpolation, linear interpolation, three convolution interpolation, polynomial interpolation, Gaussian spline interpolation, and so on. By shifting the traditional linear interpolation algorithm for the image analysis, summed up the same image interpolation linear shift the common technical defects and their causes of the theory. Then, this paper from the same linear space and image interpolation and deviation from the negative image interpolation even introduced the image of modern adaptive interpolation technology, discussed the advantages and limitations of the algorithm.
Adaptive interpolation technology transfer linear interpolation effect than the same interpolation technology have been greatly improved, but the algorithm complex calculation, the actual image processing system in the application of difficulties. This paper presents a message based on the Edge of adaptive image interpolation algorithm. According to the edge of the neighborhood image mapping, the complexity of the adaptive value of the right to adjust the interpolation image interpolation. Application of the algorithm after the interpolation of the border clear, natural, faithfully reflects the look of the original image, with the traditional interpolation algorithm compared to its borders and easy to good effect to achieve ,the experiment also proved the effectiveness of the method.
图像插值就是利用已知邻近像素点的灰度值来产生未知像素点的灰度值,以便由原始图像再生出具有更高分辨率的图像。
本文首先通过分析实际图像获取系统将图像数字化后,建立图像的模型,并给出了图像的表示方法,根据数字图像的特点阐述了图像放大的基本原理。
其次,本文介绍了传统的线性移不变插值算法。主要介绍了最近邻插值、线性插值、三次卷积插值、多项式插值、样条插值和高斯插值等。通过对传统的线性移不变图像插值算法的分析,归纳了线性移不变图像插值的共同技术缺陷和它们的理论成因。然后,论文从线性空不变图像插值和距离加偏差图像插值两方面介绍了现代自适应图像插值技术,讨论了各算法的优势和局限性。
自适应插值技术的插值效果比线性移不变插值技术有了较大的改善,但算法复杂计算量大,在实际图像处理系统中应用困难。本文提出了一种基于图像边缘信息的自适应图像插值算法。根据边缘部分映射点邻域图像的复杂程度,自适应地调节插值权值的图像插值方法。应用该算法插值后的边界清晰、自然,忠实地反映了原始图像的面貌,与传统的插值算法相比,其边界处理效果好且易于实现,实验也验证了该方法的有效性。
Today, the digital image in the field of engineering and mathematics has aroused widespread concern, and the image interpolation technology has been widely used in digital image processing, such as image zoom, image deformation, image restoration, image reconstruction.
Image Interpolation is known to use the adjacent pixels to generate unknown gray value of the gray pixels value to the original image from renewable to a higher-resolution images.
In this paper, through analysis of the actual image acquisition system will be digital image after image of the established model, and gives the image of that method, in accordance with the characteristics of digital images on the image to enlarge the basic principles.
Secondly, this paper, the traditional linear interpolation algorithm shift unchanged. Mainly on the nearest neighbor interpolation, linear interpolation, three convolution interpolation, polynomial interpolation, Gaussian spline interpolation, and so on. By shifting the traditional linear interpolation algorithm for the image analysis, summed up the same image interpolation linear shift the common technical defects and their causes of the theory. Then, this paper from the same linear space and image interpolation and deviation from the negative image interpolation even introduced the image of modern adaptive interpolation technology, discussed the advantages and limitations of the algorithm.
Adaptive interpolation technology transfer linear interpolation effect than the same interpolation technology have been greatly improved, but the algorithm complex calculation, the actual image processing system in the application of difficulties. This paper presents a message based on the Edge of adaptive image interpolation algorithm. According to the edge of the neighborhood image mapping, the complexity of the adaptive value of the right to adjust the interpolation image interpolation. Application of the algorithm after the interpolation of the border clear, natural, faithfully reflects the look of the original image, with the traditional interpolation algorithm compared to its borders and easy to good effect to achieve ,the experiment also proved the effectiveness of the method.
引文
[1] Lukin and D. Kubasov High-Quality Algorithm for Bayer Pattern Interpolation Programming and Computer Software, Vol. 30, No. 6, 2004, pp. 347 - 358.
[2] S. E. El-Khamy , M. M. Hadhoud, M.I. Dessouky, B. M. Salam , F. E. Abd El-Samie Efficient implementation of image interpolation asan inverse problem Digital Signal Processing 15 (2005) 137 - 152
[3] Dong Wook Kang, Two-channel Spatial Interpolation of Images, Signal Processing:Imag Communication, 2000(16):395-399
[4] Honda, H. ;Haseyama,M. ;Kitajima, H. , Fractal interpolation for natural images, 1999 International Conference on Image Processing, 24-28 Oct. 1999 3:657-661
[5] Shezaf, N. , Abramov-Segal,H. , Sutskover, I., Bar-Sella, R., Adaptive Low Complexity Algorithm for Image Zooming at Fractional Scaling Ratio, The 21st IEEE Convention of the Electrical and Electronic Engineers in Israel,2000:253-256
[6] Gopinath, R. A. , Burrus, C. S., Wavelet-based Lowpass Bandpass interpolation, 1992. IEEE International Conference on Acoustics, Speech, and Signal Processing,23-26 Mar. 1992,4:72 385-388
[7] Zoran Cvetkovic and Martin Vetterli,Discrete-Time Wavelet Extrema Representation:Design and Consistent Reconstruction, IEEE Trans, on Signal Processing, Mar. 1995,43(3)
[8] S. G. Chang, Image Interpolation Using Wavelet-based Edge Enhancement and Texture Analysis, M. S. thesis,University of California at Berkerly, 1995
[9] S. G. Chang, Z. Cvetkovic and M. Vetterli, Resolution Enhancement of Images Using Wavelet Transform Extrema Extrapolation, Proceedings of International Conference on Speech, Signal Processing, Detroit,May 1995,4:2379-2382.
[10]Knox Carey, W. , Chuang,D. B. ,Hemami,S. S., Regularity-Preserving Image Interpolation Proceedings of 1997 International Conference on Image Processing, 26-29 Oct. 1997,1:901-904
[11]W. Knox Carey, Daniel B. Chuang,and Sheila S. Hemami, Regularity-Preserving Image Interpolation, IEEE Trans, on Image Processing, Sep. 1999, 8(9)
[12]Nicolier, F. , Truchetet, F, Image Magnification Using Decimated Orthogonal Wavelet transform, Image Processing,Proceedings of 2000 International Conference on, 2000, 2:355-358
[13]Kentaro Kinebuchi, D. Darian Muresan,and Thomas W. Parks, Image Interpolation Using Wavelet-based Hidden Markov Trees, IEEE ICASSP 2001, Utah.
[14]Ates, H. F. , Orchard, M. T. ,Image Interpolation Using Wavelet-based Contour Estimation, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003, 3:III_109-III_112
[15]Ying Zhu, Schwartz,S. C.,Orchard,M. T., Wavelet Domain Image Interpolation via Statistical Estimation, 2001 International Conference on Image Processing, 2001, 3:840 - 843
[16]Rodrigues, L. , Leandro Borges, D. , Marcos Gonalves, L., A Locally Adaptive Edge-preserving Algorithm for Image Interpolation, 2002. Proceedings of XV Brazilian Symposium on Computer Graphics and Image Processing, 2002:300 - 305
[17]Xin Li, Orchard, M. T.,Edge Directed Prediction for Lossless Compression of Natural Images Proceedings of 1999 International Conference on Image Processing,24-28 Oct. 1999,4:58-62
[18]Xin Li, Orchard, M. T. , New Edge Directed Interpolation, Proceedings of 2000 International Conference on Image Processing,2000,2:311-314
[19]Xin Li and Michael T. Orchard, New Edge-Directed Interpolation, IEEE Trans, on Image Processing Oct 2001,10(10)
[20]F. Guichard, F. Malgouyres, Total Variation Based Interpolation, Proceedings of Eusipco' 98, 3:1741-1744
[21]Hao Jiang,Moloney,C.,A New Direction Adaptive Scheme for Image Interpolation,2002International Conference on Image Processing,24-28 June 2002,3:Ⅲ-369-Ⅲ-3
[22]Hao Jiang,Moloney,C.,Error Concealment Using a Diffusion Based Method,Proceedings of 2002 International Conference on Image Processing,22-25 Sept.2002,1:Ⅰ-832-Ⅰ-835
[23]Carrato,S.,Ramponi,G.,Marsi,S,A Simple Edge-sensitive Image Interpolation Filter,Proceedings of 1996 International Conference on Image Processing,16-19 Sep 1996,3:711-714
[24]R.Castagno and G.Ramponi,A Rational Filter For The Removal Of Blocking Artifacts In Image Sequences Coded At Low Bit rate,Proceedings of the Ⅷ European Signal Processing Conference,Trieste,Italy,Sep.1996
[25]Ramponi,G.,Carrato,S.,Interpolation of the DC Component of Coded Images Using a Rational Filter,1997 International Conference on Image Processing,26-29 Oct.19971:389-392
[26]Cheng-Soon Chuah,Jin-Jang Leou,An Adaptive Image Interpolation Algorithm for Image/Video Processing,Pattern Recognition 2001(34):2383-2393
[27]Izquierdo,E.,Image Based Rendering Using Rational Filters,Information Visualisation,2001 Proceedings of Fifth International Conference on,25-27Jul.2001:311-316
[28]Jung Woo Hwang and Hwang Soo Lee,Adaptive Image Interpolation Based on Local Gradient Features,IEEE Signal Processing Letters,Mar.2004,11(3)
[29]G.Ramponi,warped Distance for Space-Variant Linear Image Interpolation,IEEETrans.on image processing 1995(8)
[30]Jensen,K.,Anastassiou,D.,Spatial Resolution Enhancement of Images Using Nonlinear Interpolation,1990 International Conference on Acoustics,Speech,and Signal Processing,3-6 Apr 1990,4:2045-2048
[31]H.Greenspan and C.H.Anderson,Image Enhancement by Non-linear Extrapolation in Frequency Space,Proceedings of the Symposium on Electronic Imaging Science and Technology-Image and Video Processing Ⅱ,Feb.1994(2182):2-13
[32]Polesel,A.,Ramponi,G.,Mathews,V.J.,Adaptive Unsharp Masking for Contrast Enhancement,Proceedings of International Conference on Image Processing,26-29 Oct.1997,1:267-270
[33]G.Ramponi,Contrast enhancement in images via the product of linear filters,Signal Processing,77,May 1999(77):349-353.
[34]Andrea Polesel,Giovanni Ramponi,and V.John Mathews,lmage Enhancement via Adaptive Unsharp Masking,IEEE Trans.on Image Processing,Mar.2000,9(3)
[35]Cheikh,F.A.,Gabbouj,M.,Directional-rational Approach for Color Image Enhancement,2000 IEEE International Symposium on Circuits and Systems,Geneva,28-31 May 2000,3:563-566
[36]刘维一,于德月,王肇圻等 用迭代法消除数字图像放大后的模糊 光电子·激光 2002年4月 第13卷第4期
[37]庞博,张旭东,徐小红 自适应图像插值在超分辨率图像重建中的应用 合肥工业大学学报(自然科学版) 2006年7月第29卷第7期
[38]Mei-Juan Chen,Chin-Hui Huang,Wen-Li Lee A fast edge-oriented algorithm for image interpolation Image and Vision Computing 23(2005)791-798
[39]金海丁,周孝宽 数字图像自适应插值法 激光与红外 2006年9月 第36卷 第9期
[40]罗军辉,冯平,哈力旦·A等MATLAB 7.0在图像处理中的应用 北京-机械工业出版社 2005.6
[41]郑方,章毓晋编著 数字信号与图像处理 北京-清华大学出版社 2006.1
[42](日)谷口庆治编 数字图象处理 北京-科学出版社 2002.2
[43]朱秀昌等编著 数字图像处理与图像通信 北京-北京邮电大学出版社 2002.5
[44]庞博.图像插值技术及其在超分辨率图像重建中的应用:[硕士学位论文].合肥:合肥工业大学,2005
[45]马天俊.图像放大技术研究:[硕士学位论文].西安:西安电子科技大学,2004
[46]肖义男.数字图像自适应插值技术及其应用研究:[硕士学位论文].重庆:重庆大学,2005
[2] S. E. El-Khamy , M. M. Hadhoud, M.I. Dessouky, B. M. Salam , F. E. Abd El-Samie Efficient implementation of image interpolation asan inverse problem Digital Signal Processing 15 (2005) 137 - 152
[3] Dong Wook Kang, Two-channel Spatial Interpolation of Images, Signal Processing:Imag Communication, 2000(16):395-399
[4] Honda, H. ;Haseyama,M. ;Kitajima, H. , Fractal interpolation for natural images, 1999 International Conference on Image Processing, 24-28 Oct. 1999 3:657-661
[5] Shezaf, N. , Abramov-Segal,H. , Sutskover, I., Bar-Sella, R., Adaptive Low Complexity Algorithm for Image Zooming at Fractional Scaling Ratio, The 21st IEEE Convention of the Electrical and Electronic Engineers in Israel,2000:253-256
[6] Gopinath, R. A. , Burrus, C. S., Wavelet-based Lowpass Bandpass interpolation, 1992. IEEE International Conference on Acoustics, Speech, and Signal Processing,23-26 Mar. 1992,4:72 385-388
[7] Zoran Cvetkovic and Martin Vetterli,Discrete-Time Wavelet Extrema Representation:Design and Consistent Reconstruction, IEEE Trans, on Signal Processing, Mar. 1995,43(3)
[8] S. G. Chang, Image Interpolation Using Wavelet-based Edge Enhancement and Texture Analysis, M. S. thesis,University of California at Berkerly, 1995
[9] S. G. Chang, Z. Cvetkovic and M. Vetterli, Resolution Enhancement of Images Using Wavelet Transform Extrema Extrapolation, Proceedings of International Conference on Speech, Signal Processing, Detroit,May 1995,4:2379-2382.
[10]Knox Carey, W. , Chuang,D. B. ,Hemami,S. S., Regularity-Preserving Image Interpolation Proceedings of 1997 International Conference on Image Processing, 26-29 Oct. 1997,1:901-904
[11]W. Knox Carey, Daniel B. Chuang,and Sheila S. Hemami, Regularity-Preserving Image Interpolation, IEEE Trans, on Image Processing, Sep. 1999, 8(9)
[12]Nicolier, F. , Truchetet, F, Image Magnification Using Decimated Orthogonal Wavelet transform, Image Processing,Proceedings of 2000 International Conference on, 2000, 2:355-358
[13]Kentaro Kinebuchi, D. Darian Muresan,and Thomas W. Parks, Image Interpolation Using Wavelet-based Hidden Markov Trees, IEEE ICASSP 2001, Utah.
[14]Ates, H. F. , Orchard, M. T. ,Image Interpolation Using Wavelet-based Contour Estimation, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003, 3:III_109-III_112
[15]Ying Zhu, Schwartz,S. C.,Orchard,M. T., Wavelet Domain Image Interpolation via Statistical Estimation, 2001 International Conference on Image Processing, 2001, 3:840 - 843
[16]Rodrigues, L. , Leandro Borges, D. , Marcos Gonalves, L., A Locally Adaptive Edge-preserving Algorithm for Image Interpolation, 2002. Proceedings of XV Brazilian Symposium on Computer Graphics and Image Processing, 2002:300 - 305
[17]Xin Li, Orchard, M. T.,Edge Directed Prediction for Lossless Compression of Natural Images Proceedings of 1999 International Conference on Image Processing,24-28 Oct. 1999,4:58-62
[18]Xin Li, Orchard, M. T. , New Edge Directed Interpolation, Proceedings of 2000 International Conference on Image Processing,2000,2:311-314
[19]Xin Li and Michael T. Orchard, New Edge-Directed Interpolation, IEEE Trans, on Image Processing Oct 2001,10(10)
[20]F. Guichard, F. Malgouyres, Total Variation Based Interpolation, Proceedings of Eusipco' 98, 3:1741-1744
[21]Hao Jiang,Moloney,C.,A New Direction Adaptive Scheme for Image Interpolation,2002International Conference on Image Processing,24-28 June 2002,3:Ⅲ-369-Ⅲ-3
[22]Hao Jiang,Moloney,C.,Error Concealment Using a Diffusion Based Method,Proceedings of 2002 International Conference on Image Processing,22-25 Sept.2002,1:Ⅰ-832-Ⅰ-835
[23]Carrato,S.,Ramponi,G.,Marsi,S,A Simple Edge-sensitive Image Interpolation Filter,Proceedings of 1996 International Conference on Image Processing,16-19 Sep 1996,3:711-714
[24]R.Castagno and G.Ramponi,A Rational Filter For The Removal Of Blocking Artifacts In Image Sequences Coded At Low Bit rate,Proceedings of the Ⅷ European Signal Processing Conference,Trieste,Italy,Sep.1996
[25]Ramponi,G.,Carrato,S.,Interpolation of the DC Component of Coded Images Using a Rational Filter,1997 International Conference on Image Processing,26-29 Oct.19971:389-392
[26]Cheng-Soon Chuah,Jin-Jang Leou,An Adaptive Image Interpolation Algorithm for Image/Video Processing,Pattern Recognition 2001(34):2383-2393
[27]Izquierdo,E.,Image Based Rendering Using Rational Filters,Information Visualisation,2001 Proceedings of Fifth International Conference on,25-27Jul.2001:311-316
[28]Jung Woo Hwang and Hwang Soo Lee,Adaptive Image Interpolation Based on Local Gradient Features,IEEE Signal Processing Letters,Mar.2004,11(3)
[29]G.Ramponi,warped Distance for Space-Variant Linear Image Interpolation,IEEETrans.on image processing 1995(8)
[30]Jensen,K.,Anastassiou,D.,Spatial Resolution Enhancement of Images Using Nonlinear Interpolation,1990 International Conference on Acoustics,Speech,and Signal Processing,3-6 Apr 1990,4:2045-2048
[31]H.Greenspan and C.H.Anderson,Image Enhancement by Non-linear Extrapolation in Frequency Space,Proceedings of the Symposium on Electronic Imaging Science and Technology-Image and Video Processing Ⅱ,Feb.1994(2182):2-13
[32]Polesel,A.,Ramponi,G.,Mathews,V.J.,Adaptive Unsharp Masking for Contrast Enhancement,Proceedings of International Conference on Image Processing,26-29 Oct.1997,1:267-270
[33]G.Ramponi,Contrast enhancement in images via the product of linear filters,Signal Processing,77,May 1999(77):349-353.
[34]Andrea Polesel,Giovanni Ramponi,and V.John Mathews,lmage Enhancement via Adaptive Unsharp Masking,IEEE Trans.on Image Processing,Mar.2000,9(3)
[35]Cheikh,F.A.,Gabbouj,M.,Directional-rational Approach for Color Image Enhancement,2000 IEEE International Symposium on Circuits and Systems,Geneva,28-31 May 2000,3:563-566
[36]刘维一,于德月,王肇圻等 用迭代法消除数字图像放大后的模糊 光电子·激光 2002年4月 第13卷第4期
[37]庞博,张旭东,徐小红 自适应图像插值在超分辨率图像重建中的应用 合肥工业大学学报(自然科学版) 2006年7月第29卷第7期
[38]Mei-Juan Chen,Chin-Hui Huang,Wen-Li Lee A fast edge-oriented algorithm for image interpolation Image and Vision Computing 23(2005)791-798
[39]金海丁,周孝宽 数字图像自适应插值法 激光与红外 2006年9月 第36卷 第9期
[40]罗军辉,冯平,哈力旦·A等MATLAB 7.0在图像处理中的应用 北京-机械工业出版社 2005.6
[41]郑方,章毓晋编著 数字信号与图像处理 北京-清华大学出版社 2006.1
[42](日)谷口庆治编 数字图象处理 北京-科学出版社 2002.2
[43]朱秀昌等编著 数字图像处理与图像通信 北京-北京邮电大学出版社 2002.5
[44]庞博.图像插值技术及其在超分辨率图像重建中的应用:[硕士学位论文].合肥:合肥工业大学,2005
[45]马天俊.图像放大技术研究:[硕士学位论文].西安:西安电子科技大学,2004
[46]肖义男.数字图像自适应插值技术及其应用研究:[硕士学位论文].重庆:重庆大学,2005