The spatial resolution of a hyperspectral image is often coarse as the limitations on the imaging hardware. A novel super-resolution reconstruction algorithm for hyperspectral imagery (HSI) via adaptive projection onto convex sets and image blur metric (APOCS-BM) is proposed in this paper to solve these problems. Firstly, a no-reference image blur metric assessment method based on Gabor wavelet...

Image registration is an important step in all image analysis and it performs the operation of overlaying images of the alike picture taken at various times, from various viewpoints, and/or by various sensors. The wavelet domain provides invariant that are centrally symmetric to blur. Blur invariants are constructed from different wavelet function. Template image is chosen in the degraded image...

A technique to quickly detect motion blur from mobile phone camera and its implementation on an iPhone 4S were presented. GPU was utilized to accelerate the implementation. Direction of motion relative to the image space was used in addition to the image itself to detect motion blur. The accuracy of detection was 75%, and computation took on average 0.73 seconds for 8MP image on an iPhone 4S. E...

This paper presents an algorithm for a dense computation of the diierence in blur between two images. The two images are acquired by varying the intrinsic parameters of the camera. The image formation system is assumed to be passive. Estimation of depth from the blur diierence is straightforward. The algorithm is based on a local image decomposition technique using the Hermite polynomial basis....

Image motion deblurring with unknown blur kernel is an ill-posed problem. This paper proposes a blind motion deblurring approach that solves blur kernel and the latent image robustly. For kernel optimization, an edge mask is used as an image prior to improve kernel update, then an edge selection mask is adopted to improve image update. In addition, an alternative iterative method is introduced ...

In many applications, like surveillance, image sequences are of poor quality. Motion blur in particular introduces signiicant image degradation. An interesting challenge is to merge these many images into one high-quality, estimated still. We propose a method to achieve this. Firstly, an object of interest is tracked through the sequence using region based matching. Secondly, degradation of ima...

Image restoration is the process of reconstruction or recovering an image that has been corrupted by some degradation phenomenon. Degradation may occur due to motion blur, Gaussian blur, noise and camera mismatch. In this paper corrupted image have been recovered using Modified Lucy Richardson algorithm in the presence of Gaussian blur and motion blur. The performance of this algorithm has been...

Image blur kernel classification and parameter estimation are critical for blind image deblurring. Current dominant approaches use handcrafted blur features [5, 6] that are optimized for a certain type of blur, which is not applicable in real blind deconvolution where the Point Spread Function (PSF) of the blur is unknown. Inspired by the successful applications of deep learning techniques to o...

The increasing number of demanding consumer image applications has led to increased interest in no-reference objective image quality assessment (IQA) algorithms. In this paper, we propose a new blind blur index for still images based on singular value similarity. The algorithm consists of three steps. First, a re-blurred image is produced by applying a Gaussian blur to the test image. Second, a...

The image formed by the eye's optics is inherently blurred by aberrations specific to the individual's eyes. We examined to what extent judgments of perceived focus depend on the total magnitude as opposed to the specific pattern of blur introduced by the eye's high order aberrations (HOA). An Adaptive Optics system was used to simultaneously correct each subject's wave aberrations and display...