Regularization in global sound equalization based on effort variation

Regularization in global sound equalization based on effort variation.

Sound equalization in closed spaces can be significantly improved by generating propagating waves that are naturally associated with the geometry, as, for example, plane waves in rectangular enclosures. This paper presents a control approach termed effort variation regularization based on this idea. Effort variation equalization involves modifying the conventional cost function in sound equaliz...

Power-output regularization in global sound equalization (L)

Total Variation Regularization in Digital Breast Tomosynthesis: Regularization Parameter Determination based on Small Structures Segmentation Rates

Regularization approaches for the limited-angle reconstruction problem in digital breast tomosynthesis are widelyused. Though, their benefits depend largely upon a suitable regularization parameter estimation. We aim to evaluate the reconstruction quality of precise small contrast features objectively with the help of an automated process. These features were represented by so-called Landolt ri...

A Super-Resolution Algorithm Based on Adaptive Total Variation Regularization

An algorithm with L1 and L2 mixed norm and bilateral total variation(BTV) regularization is proposed in this paper for image super-resolution. First, the mixed norm is used as the constraint of image fidelity; Secondly, considering the effect of the BTV method is not ideal for reconstruction in the edge and texture region, an adaptive regularization parameter algorithm is proposed. In the propo...

Total-Variation Based Piecewise Affine Regularization

We introduce a novel second-order regularizer, the Affine Total-Variation term, to capture the geometry of piecewise affine functions. The approach is characterized by two convex decompositions of a given image into piecewise affine structure and texture and noise, respectively. A convergent multiplier-based method is presented for computing a global optimum by computationally cheap iterative s...