Adaptive and Non-adaptive Image Interpolation Techniques

2015 ◽  
Author(s):  
Shruti H. Mahajan ◽  
Varsha K. Harpale
Keyword(s):  
Image Interpolation ◽  
Interpolation Techniques

scholarly journals A Block-Based Regularized Approach for Image Interpolation

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Li Chen ◽  
Xiaotong Huang ◽  
Jing Tian
Keyword(s):  
Cost Function ◽  
Regularization Parameter ◽  
Computational Cost ◽  
Closed Form Solution ◽  
Image Interpolation ◽  
Adaptive Strategy ◽  
Form Solution ◽  
Interpolation Techniques ◽  
Block Based ◽  
Value Decomposition

This paper presents a new efficient algorithm for image interpolation based on regularization theory. To render ahigh-resolution(HR) image from alow-resolution(LR) image, classical interpolation techniques estimate the missing pixels from the surrounding pixels based on a pixel-by-pixel basis. In contrast, the proposed approach formulates the interpolation problem into the optimization of a cost function. The proposed cost function consists of a data fidelity term and regularization functional. The closed-form solution to the optimization problem is derived using the framework of constrained least squares minimization, by incorporating Kronecker product andsingular value decomposition(SVD) to reduce the computational cost of the algorithm. The effect of regularization on the interpolation results is analyzed, and an adaptive strategy is proposed for selecting the regularization parameter. Experimental results show that the proposed approach is able to reconstruct high-fidelity HR images, while suppressing artifacts such as edge distortion and blurring, to produce superior interpolation results to that of conventional image interpolation techniques.

A NEW APPROACH FOR ADAPTIVE POLYNOMIAL BASED IMAGE INTERPOLATION

2006 ◽  
Vol 03 (02) ◽  
pp. 139-159 ◽  
Author(s):  
S. E. EL-KHAMY ◽  
M. M. HADHOUD ◽  
M. I. DESSOUKY ◽  
B. M. SALAM ◽  
F. E. ABD EL-SAMIE
Keyword(s):  
Adaptive Algorithm ◽  
Signal To Noise Ratio ◽  
Estimation Error ◽  
Computational Cost ◽  
Image Interpolation ◽  
Point Of View ◽  
Edge Preservation ◽  
Adaptive Interpolation ◽  
Pixel Value ◽  
Interpolation Techniques

In this paper, an adaptive algorithm is suggested for the implementation of polynomial based image interpolation techniques such as Bilinear, Bicubic, Cubic Spline and Cubic O-MOMS. This algorithm is based on the minimization of the squared estimation error at each pixel in the interpolated image by adaptively estimating the distance of the pixel to be estimated from its neighbors. The adaptation process at each pixel is performed iteratively to yield the best estimate of this pixel value. This adaptive interpolation algorithm takes into consideration the mathematical model by which a low resolution (LR) image is obtained from a high resolution (HR) image. This adaptive algorithm is compared to traditional polynomial based interpolation techniques and to the warped distance interpolation techniques. The performance of this algorithm is also compared to the performance of other algorithms used in commercial interpolation softwares such as the ACDSee and the Photopro programs. Results show that the suggested adaptive algorithm is superior from the Peak Signal to Noise Ratio (PSNR) point of view to other traditional techniques and it has a higher ability of edge preservation than traditional image techniques. The computational cost of the adaptive algorithm is studied and found to be moderate.

Task-specific evaluation of 3D image interpolation techniques

1998 ◽  
Author(s):  
George J. Grevera ◽  
Jayaram K. Udupa ◽  
Yukio Miki
Keyword(s):  
Image Interpolation ◽  
3D Image ◽  
Interpolation Techniques ◽  
Specific Evaluation

scholarly journals A Multi-Phasic Perspective of the Intact Permeability of the Heterogeneous Argillaceous Cobourg Limestone

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
A. P. S. Selvadurai
Keyword(s):  
Digital Imaging ◽  
Effective Permeability ◽  
Computational Models ◽  
Clay Fraction ◽  
Image Interpolation ◽  
Argillaceous Rock ◽  
Factors Influencing ◽  
Surface Image ◽  
Interpolation Techniques

AbstractThe Cobourg limestone is a heterogeneous argillaceous rock consisting of lighter nodular regions of calcite and dolomite, interspersed with darker regions composed of calcite, dolomite, quartz and a clay fraction. The intact permeability of the Cobourg limestone is estimated to be in the range of K ∈ (10−23, 10−19) m2. This paper discusses the factors influencing the measurement of the intact permeability of the Cobourg limestone and presents an upscaling approach for estimating this parameter. The procedure first involves the dissection of a cuboidal sample of the rock measuring, 80 mm × 120 mm × 300 mm, into ten 8 mm-thick slabs. Digital imaging and mapping of the larger surfaces of these sections are used to create, from both surface image extrusion and surface image interpolation techniques, the fabric within the dissected regions. The estimated permeabilities of the lighter and darker regions are used in the computational models of the computer-generated fabric to estimate the effective permeability of the rock. These results are complemented by estimates derived from mathematical theories for estimating permeabilities of multiphasic composites.

scholarly journals FPGA Implementation of Adaptive Multiplier-Based Linear Image Interpolation

2019 ◽  
Vol 8 (10) ◽  
pp. 551-557
Keyword(s):  
Signal To Noise Ratio ◽  
Similarity Index ◽  
Image Interpolation ◽  
Structural Similarity ◽  
Linear Interpolation ◽  
Low Complexity ◽  
Adaptive Interpolation ◽  
Field Programmable ◽  
Interpolation Techniques

This work provides an image interpolation for multimedia applications by utilizing an adaptive multiplier-based stepwise linear interpolation with clam filter. Image interpolation is also termed as image up-scaling. Generally, while enlarging an image some vacant bit positions are introduced and due to this empty pixel positions, the quality of the image is decreased. Therefore to maintain the quality of the image, new pixels are introduced and those pixels are used to fill the vacant bit positions by using interpolation techniques. In the adaptive interpolation techniques, edge pixels are identified and filtered at prior to the interpolation process. This will improve the quality of the interpolated image. However, the adaptive interpolation scheme increases the complexity of the system. To reduce the complexity, this work uses low complexity stepwise linear interpolation and to maintain the quality it uses multiplier-based linear stepwise (MBLSI) and edge enhancement technique. The experimental results demonstrate that the complexity of the proposed work is less as compared with other related work as well as the quality is also maintained. The proposed work utilizes 275 LUTs to provide the average peak signal to noise ratio (PSNR) of 20.44 dB and structural similarity index (SSIM) as 0.8250. This proposed work increases the PSNR by 0.89 dB from the conventional multiplier-based stepwise linear interpolation. Further the proposed interpolation algorithm utilizes less number of resources in field programmable gate array (FPGA) by comparing with other related interpolation techniques.

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