The design of linear image filters based on properties of human visual perception has been shown to require the minimization of criterion functions in both the spatial and frequency domains. We extend this approach to continuous filters of infinite support. For lowpass filters, this leads to the concept of an ideal lowpass image filter that provides a response that is superior perceptually to that of the classical ideal lowpass filter. >

/pdf/linear-filtering-of-images-based-on-properties-of-vision-27auserke0.pdf

Linear filtering of images based on properties of vision

In this paper we derive an optimal (MMSE) prefilter for image interpolation. This derivation is based upon a model of the sensor used to capture the image. To employ this model, we restate the interpolation problem in an intuitive, reconstruction-like fashion. Using a simple CCD sensor model, an example prefilter is derived. Simulations with this prefilter are performed using linear and cubic interpolation as well as an ad hoc, directional interpolation scheme. Quantitative and subjective results indicate that prefiltering generally improves the quality of the interpolated images.

Optimal prefiltering for improved image interpolation

This paper presents a new approach to single-image super resolution by a simple and fast image interpolation method based on the combination of three different procedures. In the first phase of five phase algorithm, determination, marking and interpolation of the edges of the image is done. In second phase, the interpolated values are modified using a refinement procedure that reduces the zigzag and staircase appearance in the curved edges. In the third phase, moving average interpolation is applied to the positions of empty pixels so as to estimate the non-edge pixels with color information from surrounding neighbor pixels. The complete set of steps involved in the method results in super resolved images with a comparable appearance like that of original LR image, with much detail and least artifacts which transpire with previous methods. The colors in the various patterns are not spilled out or mixed into areas of contrasting colors, thus reducing edge blurring and providing a smooth and presentable natural-image. The proposed method shows better performance over existing approaches in PSNR value test conducted on a wide series of images in terms of computation complexity, turn-around time and quality of output. This implementation has far less computational complexities and is well suited for applications that need low turn-around time.

http://tudr.thapar.edu:8080/jspui/bitstream/10266/3296/4/3296.pdf

Image super resolution by fast edge-adaptive interpolation

The objective of this paper is to introduce a new integrated methodology for iris detection and recognition using a two fold method to deduce better results as compared to the existing techniques. The methodology primarily employs the Finite Impulse Response(FIR) and Gabor wavelet transform as for computing fundamentals. The figurative classification in the proposed algorithm is on the basis of euclidean distance. Thus the proposed algorithm solely works on construing the euclidean distances of the test sample with respect to that of the samples in the data set in the either fold procedures. Further the least euclidean distance measured is considered as the perfect match for the input test sample. As a result of extensive testing and implementation of the proposed algorithm/methodology in this paper, satisfactory accuracy and results are obtained as tested on Self Generated Dataset. The proposed algorithm focus on extensively using all the data available and retrievable from the human iris, specifically the red, green and blue segments, i.e RGB scheme unlike traditional iris based recognition wiz. computation on grayscale inputs, thus on the contrary, the methodology presented in this paper employs suitable color coding pattern using FIR(Finite Impulse Response) in addition to the Gabor filter texture classification technique.

Iris detection and recognition using 2 fold technique

http://tudr.thapar.edu:8080/jspui/bitstream/10266/846/3/846%20Mayank%20Kumar%20%2880732013%29.pdf

An Adaptive Zooming Algorithm for Images

Image interpolation is an important image operation. It is commonly used in image enlargement to obtain a close-up view of the detail of an image. From sampling theory, an ideal low-pass filter can be used for image interpolation. However, ripples appear around image edges which are annoying to a human viewer. The authors introduce a new FIR image interpolation filter known as a perceptually weighted least square (PWLS) filter which is designed using both sampling theory and properties of human vision. The goal of this design approach is to minimize the ripple response around edges of the interpolated images and to best satisfy frequency response constraints. The interpolation results using the proposed approach are substantially better than those resulting from replication or bilinear interpolation, and are at least as good as and possibly better than that of cubic convolution interpolation. >

Hong Chen

Papers

An FIR image interpolation filter design method based on properties of human vision