## Adaptively quadratic (AQua) image interpolation (2004)

Venue: | IEEE Transactions on Image Processing |

Citations: | 23 - 1 self |

### BibTeX

@ARTICLE{Muresan04adaptivelyquadratic,

author = {D. Darian Muresan and Thomas W. Parks and D. Darian and Muresan Digital and Multi Media Design},

title = {Adaptively quadratic (AQua) image interpolation},

journal = {IEEE Transactions on Image Processing},

year = {2004},

volume = {13},

pages = {690--698}

}

### OpenURL

### Abstract

Image interpolation is a key aspect of digital image processing. This paper presents a novel interpolation method based on optimal recovery and adaptively determining the quadratic signal class from the local image behavior. The advantages of the new interpolation method are the ability to interpolate directly by any factor and to model properties of the data acquisition system into the algorithm itself. Through comparisons with other algorithms it is shown that the new interpolation is not only mathematically optimal with respect to the underlying image model, but visually it is very efficient at reducing jagged edges, a place where most other interpolation algorithms fail. Index Terms image modeling, quadratic classes, interpolation I.

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Citation Context ...re than the image itself. The image models of [15] are similar in nature. The authors of [16] model the wavelet coefficients using Gaussian mixtures and apply their models to image denoising [17]. In =-=[18]-=- the image model of [16] is extended to image interpolation. For this interpolation method the interpolation results are comparable with bi-cubic interpolation. One particular feature of this approach... |

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Citation Context ...d the local weights. This method works for interpolation by factors of two and performs well around edges, but performs poorly in high frequency regions, sometimes introducing undesired artifacts. In =-=[22]-=- it is shown how this solution can be reformulated using optimal recovery which allows for additional assumptions about the local derivatives in addition to the known local pixels to be used in the in... |

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Citation Context ... under-sampled images. Their expansion method could be used for a single image by assuming only one frame. Applying the algorithm to a single frame results in images very similar to those of [19]. In =-=[21]-=- the authors present a least squares edge directed interpolation method. The method assumes that each pixel is a linear combination of its neighboring pixels. Further, it is assumed that locally the w... |

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Citation Context ...from the local neighborhood. A second approach is to use patches from other high density images. This works well when interpolating images that belong to a certain predetermined class. For example in =-=[24]-=- AQua interpolation is applied to face interpolation and the training set is determined from other high resolution faces. A third approach is to adaptively search for training patches in other high re... |

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Citation Context ...ndrill, andpeppers. Therings image is 256 × 256 and consists of concentric circles that get closer and closer to each other as they move outward, away from the origin. The rings image is suggested by =-=[26]-=- for visualizing the results of applying different interpolation filters. Images barbra, lena, mandrill, andpeppers are 512 × 512 gray scale images available from [27]. All images are gray scale image... |

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Citation Context ...erpolation against four other interpolation techniques. Section V concludes with final remarks and future research work in this area. Finally, the Appendix reviews the theory of optimal recovery [1], =-=[2]-=-, which is key to the problem of interpolating missing samples in a quadratic signal class. II. REVIEW In the area of image interpolation by far the most well known and widely used techniques are thos... |

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Citation Context ...n be reformulated using optimal recovery which allows for additional assumptions about the local derivatives in addition to the known local pixels to be used in the interpolation process. The work of =-=[23]-=- is related to our image interpolation approach. The authors pose the image interpolation problem as one where the image belongs to a fixed quadratic image class. To solve the interpolation problem th... |

1 |
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Citation Context ...ifacts more than the image itself. The image models of [15] are similar in nature. The authors of [16] model the wavelet coefficients using Gaussian mixtures and apply their models to image denoising =-=[17]-=-. In [18] the image model of [16] is extended to image interpolation. For this interpolation method the interpolation results are comparable with bi-cubic interpolation. One particular feature of this... |