the goal of multi-frame super resolution (sr) is to fuse multiple low resolution (lr) images to produce one high resolution (hr) image. the major challenge of classic sr approaches is accurate motion estimation between the frames. to handle this challenge, fuzzy motion estimation method has been proposed that replaces value of each pixel using the weighted averaging all its neighboring pixels i...

In this research, we have proposed the central-symmetrical property of image reconstructions from Zernike moments and pseudo-Zernike moments. We conducted the image reconstructions from the odd, even, and complete sets of Zernike moments and pseudo-Zernike moments, and verified the proposed central-symmetrical property. We have concluded that if the original image is centrally symmetrical, the ...

Zernike moments are complex moments with the orthogonal Zernike polynomials as kernel function, compared with other moments; Zernike moments have greater advantages in image rotation and low noise sensitivity. Because of the Zernike moments have image rotation invariance, and can construct arbitrary high order moments, it can be used for target recognition. In this paper, the Zernike moment alg...

Zernike moments are widely used in several pattern recognition applications, as invariant descriptors of the image shape. Zernike moments have proved to be superior than other moment functions in terms of their feature representation capabilities. The major drawback with Zernike moments is the computational complexity. This paper presents a fast algorithm for the computation of Zernike moments ...

This paper presents a novel approach to the fast computation of Zernike moments from a digital image. Most existing fast methods for computing Zernike moments have focused on the reduction of the computational complexity of the Zernike 1-D radial polynomials by introducing their recurrence relations. Instead, in our proposed method, we focus on the reduction of the complexity of the computation...

Pseudo-Zernike moments have better feature representation capabilities and are more robust to image noise than the conventional Zernike moments. However, pseudo-Zernike moments have not been extensively used as feature descriptors due to the computational complexity of the pseudo-Zernike radial polynomials. This paper discusses the drawbacks of the existing methods, and proposes an efficient re...

Received July 7, 1993; revised manuscript received November 22, 1993; accepted December 14, 1993 We propose orthogonal Fourier-Mellin moments, which are more suitable than Zernike moments, for scaleand rotation-invariant pattern recognition. The new orthogonal radial polynomials have more zeros than do the Zernike radial polynomials in the region of small radial distance. The orthogonal Fourier...

Most of the sub-pixel edge detection methods proposed in literature are based on Ghosal and Mehrotra’s method which uses Zernike moments. Some research has been reported using Fourier-Mellin moments for sub-pixel edge detection. Pseudo Zernike moments have been proved to be superior to Zernike moments in terms of their feature representation capabilities and sensitivity to image noise. This pap...

The Zernike moment algorithm and R-Tree algorithm are known as state of the art in the recognition of images and in the multimedia database respectively. The methods of storing the images and retrieving the similar images based on a query image automatically are the problems in the image database. This paper proposes the method to combine the Zernike moments algorithm and the R–tree algorithm i...

problem statement: Digital image watermarking is the most popular method for image authentication, copyright protection and content description. Zernike moments are the most widely used moments in image processing and pattern recognition. The magnitudes of Zernike moments are rotation invariant so they can be used just as a watermark signal or be further modified to carry embedded data. The com...