Blur estimation in image processing has come to be of great importance in assessing the quality of images. This work presents a survey of no-reference blur estimation methods. A no-reference method is particularly useful, when the input image used for blur estimation does not have an available corresponding reference image. This paper provides a comparison of the methodologies of four no-refere...

We describe a new no-reference blur index for still images based on a singular value curve (SVC). The algorithm is composed of two steps. First, the singular value decomposition is performed on the image to be blur-assessed. Then an image blur index is constructed from the singular value curve. Experimental results obtained on four simulated blur databases and on the Real Blur Image Database sh...

This paper presents a no-reference image quality measure, targeted towards blur distortions based on the study of human blur perception for varying contrast values. Utilizing sensitivity of human blur perception at different contrasts, a probabilistic framework is developed. This framework is used to estimate the probability of detecting blur at each edge in an image. The blur perception inform...

The point spread function (PSF) of a blurred image is often unknown a priori; the blur must first be identified from the degraded image data before restoring the image. Generalized cross-validation (GCV) is introduced to address the blur identification problem. The GCV criterion identifies model parameters for the blur, the image, and the regularization parameter, providing all the information ...

In image deconvolution or restoration using Kalman filter, the image and blur models are required to be known for the restoration process. Generally, the accuracy of the restoration depends on the accuracy of the given models. Unfortunately, the image and blur models are normally unknown in practice. To solve the problem, an identification stage is employed to estimate the image and blur models...

To use a projector anytime anywhere, a lot of projectorcamera based approaches have been proposed. In this paper, we focus on a focal correction technique, one of projector-camera based approaches, reduces an effect of defocus blur which occurs when a screen is located out of projector’s depth-of-field. We propose a novel method for estimating projector defocus blur on a planar screen without a...

Resizing to a lower resolution can alter the appearance of an image. In particular, downsampling an image causes blurred regions to appear sharper. It is useful at times to create a downsampled version of the image that gives the same impression as the original, such as for digital camera viewfinders. To understand the effect of blur on image appearance at different image sizes, we conduct a pe...

In this paper, we address the problem of jointly estimating the latent image and the depth/blur map from a single space-variantly blurred image using dictionary learning. The approach taken is based on the central idea of dictionary replacement viz. the sparse representation of a blurred image over a blurred dictionary is equivalent to that over a clean dictionary. While most of the dictionary-...

The blurred images will make image processing difficult and be hard to get high image solution for recognition, which will lower the precision of a variable rate spray system in pesticide application. In this paper, Radon transform in frequency domain is used in this work to test the blur angle and blur length in different tractors speeds and camera heights. Four image restoration methods in te...

In this paper, we address the problem of jointly estimating the latent image and the depth/blur map from a single space-variantly blurred image using dictionary replacement. While most of the dictionary-based deblurring methods consider planar scenes with spaceinvariant blur, we handle 3D scenes with spacevariant blur caused by either camera motion or optical defocus. For a given blurred image,...