Edge Directed Resolution Enhancement and Demosaicing

Project Name: Machine Learning Methods for Demosaicing and Super-resolution

Related Work: For the traditional methods of demosaicing we mentioned the low-pass-filtered chrominance method in the lecture. We can use Gaussian filter or bilateral filter [1] as our low-pass filter. Another approach is edge-directed interpolation, which is proposed by Gunturk et al [2], it tries to interpolate the image based on the direction of edges, to preserve the edge sharpness. We a...

Simultaneous demosaicing and resolution enhancement from under-sampled image sequences

Low-complexity color demosaicing algorithm based on integrated gradients

bstract. Color demosaicing is critical for digital cameras, because t converts a Bayer sensor mosaic output to a full color image, which etermines the output image quality of the camera. In this work, an fficient decision-based demosaicing method is presented. This ethod exploits a new edge-sensing measure called integrated graient (IG) to effectively extract gradient information in both color ...

A Low Complexity Color Demosaicing Algorithm Based on Integrated Gradient

Color demosaicing is critical to digital cameras as it converts a Bayer sensor mosaic output to a full color image, which determines the output image quality of the camera. In this paper, an efficient decision-based demosaicing method is presented. This method exploits a new edge-sensing measure called integrated gradient (IG) to effectively extract gradient information in both color intensity ...

BLADE: Filter Learning for General Purpose Image Processing

The Rapid and Accurate Image Super Resolution (RAISR) method of Romano, Isidoro, and Milanfar is a computationally efficient image upscaling method using a trained set of filters. We describe a generalization of RAISR, which we name Best Linear Adaptive Enhancement (BLADE). This approach is a trainable edge-adaptive filtering framework that is general, simple, computationally efficient, and use...