Some remarks on cone-adapted shearlets

This paper presents a novel method for image denoising based on the undecimated double density dual tree discrete wavelet transform (UDDDT-DWT). The critically sampled discrete wavelet transform (DWT) suffers from the drawbacks of being shift-variant and lacking the capacity to process directional information in images. The double density dual tree discrete wavelet transform (DDDT-DWT) is an approximately shift-invariant transform capturing directional information. The UDDDT-DWT is an improvement of the DDDT-DWT, making it exactly shift-invariant. An adaptive threshold is found by analyzing the statistical parameters of each subband and it is applied using modified soft thresholding. Experimental results over a range of noise variances indicate that proposed method performs better than other state of the art methods considered. This paper presents a novel method for image denoising based on the undecimated double density dual tree discrete wavelet transform (UDDDT-DWT). The critically sampled discrete wavelet transform (DWT) suffers from the drawbacks of being shift-variant and lacking the capacity to process directional information in images. The double density dual tree discrete wavelet transform (DDDT-DWT) is an approximately shift-invariant transform capturing directional information. The UDDDT-DWT is an improvement of the DDDT-DWT, making it exactly shift-invariant. An adaptive threshold is found by analyzing the statistical parameters of each subband and it is applied using modified soft thresholding. Experimental results over a range of noise variances indicate that proposed method performs better than other state of the art methods considered.

In this paper, an undecimated double density dual tree discrete wavelet transform (UDDDT-DWT) based image resolution enhancement technique is proposed. The critically sampled discrete wavelet transform (DWT) suffers from the drawbacks of being shift-variant and lacking the capacity to process directional information in images. The double density dual tree wavelet transform (DDDT-WT) is an approximately shift-invariant transform capturing directional information. The UDDDT-DWT is an improvement of the DDDT-DWT, making it exactly shift-invariant. The method uses a forward and inverse (UDDDT-DWT) to construct a high-resolution (HR) image from the given lower-resolution (LR) image. The HR image is reconstructed from the LR image using the inverse UDDDT-DWT. Results are presented and discussed through comparisons between state-of-the-art resolution enhancement methods.

Shearlet coorbit spaces and associated Banach frames

Dresses are usually created to clothe bodies, to be worn, to hide a body, to reveal parts of a body or cause a body to move in a particular way due to weight or restrictions. Dresses can represent particular cultures, identities or personas. Dresses in or as art (dress-art) are shifted from their intentions for actual bodies to material and aesthetic transformations. Examples of dress-art, created by eight different artists around the world, are discussed. Space and place theories, dress scholarship, embodiment and ideas from both Karen Barad and Judith Butler frame the discussion. Cultural, social and material insights along with self and identity are explored with reference to senses of place, space and identity for the artist, the viewer and the artworks themselves. Artists discussed in this chapter have engaged form, cultural and material aspects of dresses and presented or performed these works and in doing so, offered an opportunity to discuss how dress-art unsettles place and space. Some examples include dress-art that features dresses without bodies wearing them, dresses that suggest bodily space in its physical form but are more about embodied, imagined form, empty space or an absence or a void of the body the dress is designed to encase, cover or adorn.

Blind image deblurring, one of the main problems in image restoration, is a challenging, ill-posed problem. Hence, it is important to design a prior to solve it. Recently, deep image prior (DIP) has shown that convolutional neural networks (CNNs) can be a powerful prior for a single natural image. Previous DIP-based deblurring methods exploited CNNs as a prior when solving the blind deburring problem and performed remarkably well. However, these methods do not completely utilize the given multiple blurry images, and have limitations of performance for severely blurred images. This is because their architectures are strictly designed to utilize a single image. In this paper, we propose a method called DualDeblur, which uses dual blurry images to generate a single sharp image. DualDeblur jointly utilizes the complementary information of multiple blurry images to capture image statistics for a single sharp image. Additionally, we propose an adaptive L2_SSIM loss that enhances both pixel accuracy and structural properties. Extensive experiments show the superior performance of our method to previous methods in both qualitative and quantitative evaluations.

No-reference image quality assessment in contourlet domain

Compressive sensing (CS) is a radical new way of sampling signal at a sub-Nyquist rate, acquires a signal of interest indirectly by correcting a very limited number of its “projections”, and the signal can be exactly reconstructed from these “projections”, this new signal acquisition paradigm has revolutionized the way digital data are traditionally acquired. Generally, researchers always use orthogonal wavelet as sparse basis, but it fails to provide an optimal sparse representation for images that contain texture details. In this paper, we use shearlet which is a new directional multiresolution transform, can efficiently represent the directional information of images, meanwhile, using the RecPF of [4] as the reconstruction algorithm. The experimental results indicate that the quality of reconstructed image is improved and obtain better performance of PSNR.KeywordsCompressive sensingwaveletshearletRecPFPSNR

Effects of thermal cycling parameters on residual stresses in alumina scales of CoNiCrAlY and NiCoCrAlY bond coats

Coorbit spaces for dual pairs

Design and development of ceramic-based composites with tailored properties for cutting tool inserts

In this paper we propose a general coorbit space theory suitable to define coorbits of quasi-Banach spaces using an abstract continuous frame, indexed by a locally compact Hausdorff space, and an associated generalized voice transform. The proposed theory realizes a further step in the development of a universal abstract theory towards various function spaces and their atomic decompositions which has been initiated by Feichtinger and Grochenig in the late 1980s. We combine the recent approaches in Rauhut and Ullrich (J Funct Anal 260(11):3299–3362, 2011) and Rauhut (Stud Math 180(3):237–253, 2007) to identify, in particular, various inhomogeneous (quasi-Banach) spaces of Besov–Lizorkin–Triebel type. To prove the potential of our new theory we apply it to spaces with variable smoothness and integrability which have attracted significant interest in the last 10 years. From the abstract discretization machinery we obtain atomic decompositions as well as wavelet frame isomorphisms for these spaces.

Characterization of crystal structure and microwave dielectric properties of AZrNb2O8 (A=Zn, Co, Mg, Mn) ceramics based on complex bond theory

Frame permutation quantization (FPQ) is a new vector quantization technique using finite frames. In FPQ, a vector is encoded using a permutation source code to quantize its frame expansion. This means that the encoding is a partial ordering of the frame expansion coefficients. Compared to ordinary permutation source coding, FPQ produces a greater number of possible quantization rates and a higher maximum rate. Various representations for the partitions induced by FPQ are presented and reconstruction algorithms based on linear programming and quadratic programming are derived. Reconstruction using the canonical dual frame is also studied, and several results relate properties of the analysis frame to whether linear reconstruction techniques provide consistent reconstructions. Simulations for Gaussian sources show performance improvements over entropy-constrained scalar quantization for certain combinations of vector dimension and coding rate.

We have investigated the structural, elastic and thermodynamic properties of CaX (X = S, Se, and Te) using first-principles calculations. The exchange-correlation functional employed is the generalized gradient approximation of Wu and Cohen (GGA-WC). The estimated structural properties of these compounds are in excellent agreement with experimental data. The stability of the compounds was discussed on basis of the calculated elastic constants Cij, which are in good agreement with the experimental results. The thermodynamic properties of CaX materials are also calculated. Furthermore, the effects of temperature and pressure upon the heat capacities, expansion coefficients and bulk modulus have been calculated and discussed.

Assessment of structural, thermal, and mechanical properties of portlandite through molecular dynamics simulations