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A generalized framework for numerical differentiation (ND) is proposed for constructing a finite impulse response (FIR) filter in closed form. The framework regulates the frequency response of ND filters for arbitrary derivative-order and cutoff frequency selected parameters relying on interpolating power polynomials and maximally flat design techniques. Compared with the state-of-the-art solutions,...
We introduce a new exponential-based shift-invariant approach to image interpolation using stochastic modeling. Our model stems from Sobolev reproducing kernels of exponential type, motivated by their role in continuous-domain stochastic autoregressive processes. An algorithm based on these tools is developed and tested. Experimental results of image and texture scaling show that these exponential...
The traditional approach to image interpolation is by synthesis using basis functions because of its computational simplicity and experience-proven quality of the result. We offer an alternative approach to designing the basis (interpolation kernels), using least-squares optimisation and image models that encompass the prior knowledge. In this paper we consider and derive a finite-support interpolation...
With the increasing use of digital monitor technique, requirements for image interpolation have become more critical. However, the traditional algorithms have several serious disadvantages. First of all, the blocking effect and poor quality exist throughout the results. Therefore, edge detect method has been widely used for the image scaling up techniques but is notorious for its high complexity and...
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