Adaptive Markov Random Fields for Example-Based Super-resolution of Faces
نویسندگان
چکیده
منابع مشابه
Adaptive Markov Random Fields for Example-Based Super-resolution of Faces
Image enhancement of low-resolution images can be done throughmethods such as interpolation, super-resolution using multiple video frames, and example-based super-resolution. Example-based super-resolution, in particular, is suited to images that have a strong prior (for those frameworks that work on only a single image, it is more like image restoration than traditional, multiframe super-resol...
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Suppose we want to digitally enlarge a photograph. The input is a single, low-resolution image, and the desired output is an estimate of the high-resolution version of that image. This problem can be phrased as one of “image interpolation”: we seek to interpolate the pixel values between our observed samples. Image interpolation is sometimes called super-resolution, since we are estimating data...
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The Problem: Pixel representations for images do not have resolution independence. When we zoom into a bitmapped image, we get a blurred image. Figure 1 shows the problem for a teapot image, rich with real-world detail. We know the teapot’s features should remain sharp as we zoom in on them, yet standard pixel interpolation methods, such as pixel replication (b, c) and cubic spline interpolatio...
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Example-based super-resolution has become increasingly popular over the last few years for its ability to overcome the limitations of classical multi-frame approach. In this paper we present a new examplebased method that uses the input low-resolution image itself as a search space for high-resolution patches by exploiting self-similarity across different resolution scales. Found examples are c...
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We address the super-resolution problem: how to estimate missing high spatial frequency components of a static image. From a training set of fulland lowresolution images, we build a database of patches of corrsponding highand low-frequency image information. Given a new low-resolution image to enhance, we select from the training data a set of 10 candidate high-frequency patches for each patch ...
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ژورنال
عنوان ژورنال: EURASIP Journal on Advances in Signal Processing
سال: 2006
ISSN: 1687-6180
DOI: 10.1155/asp/2006/31062