Applications of the linear canonical transform to digital image processing.

In this paper, an existing approximation of discrete linear canonical transform (DLCT) is analyzed, and constraints are derived to fulfill some paramount properties as inversibility and additivity or the possibility to perform classical image operations in the frequency domain as image filtering. Giving some special values to the DLCT parameters and taking advantage of the division of the image spectrum in four zones of different significance, an application of image feature classifications is successfully investigated. Also, the required constraints are obtained to determine the suitability of the selected approximation when working with digital images.

No-reference image quality assessment through the von Mises distribution.

An innovative way of calculating the von Mises distribution of image entropy is introduced in this paper. The von Mises distribution's concentration parameter and some fitness parameter that will be defined later have been analyzed in the experimental part for determining their suitability as an image quality assessment measure in some particular distortions such as Gaussian blur or additive Gaussian noise. To achieve such measure, the local Rényi entropy is calculated in four equally spaced orientations and used to determine the parameters of the von Mises distribution of the image entropy.

Anisotropy-based robust focus measure for non-mydriatic retinal imaging.

Non-mydriatic retinal imaging is an important tool for diagnosis and progression assessment of ophthalmic diseases. Because it does not require pharmacological dilation of the patient's pupil, it is essential for screening programs performed by non-medical personnel. A typical camera is equipped with a manual focusing mechanism to compensate for the refractive errors in the eye.

Discrimination of isotrigon textures using the Rényi entropy of Allan variances.

We present a computational algorithm for isotrigon texture discrimination. The aim of this method consists in discriminating isotrigon textures against a binary random background. The extension of the method to the problem of multitexture discrimination is considered as well.

Blind image quality assessment through anisotropy.

We describe an innovative methodology for determining the quality of digital images. The method is based on measuring the variance of the expected entropy of a given image upon a set of predefined directions. Entropy can be calculated on a local basis by using a spatial/spatial-frequency distribution as an approximation for a probability density function.