Coding Gain and Tuning for Parametrized Visual Quality Metrics

Author(s):  
S. de Waele ◽  
M. J. Verberne
2016 ◽  
Vol 2016 (15) ◽  
pp. 1-10 ◽  
Author(s):  
Oleg I Ieremeiev ◽  
Vladimir V Lukin ◽  
Nikolay N Ponomarenko ◽  
Karen O Egiazarian ◽  
Jaakko Astola

Author(s):  
Andrada Tatu ◽  
Peter Bak ◽  
Enrico Bertini ◽  
Daniel Keim ◽  
Joern Schneidewind

2021 ◽  
Vol 6 (2) ◽  
pp. 119
Author(s):  
Awaludin Abid ◽  
Kusrini Kusrini ◽  
Amir Fatah Sofyan

Di Industri otomotif, biaya prototyping meningkat berbanding lurus dengan kompleksitas dan dependensi kendaraan. Sebagai alternatif untuk prototyping fisik dapat memanfaatkan teknologi baru seperti Augmented Reality (AR) dan Virtual Reality (VR) digunakan. Penggunaan VR dan AR melibatkan real-time rendering data CAD yang mengkonsumsi banyak memori dan mengurangi kinerja aplikasi. Persiapan data memiliki peran penting untuk meningkatkan kinerja sementara tetap mempertahankan topologi dan kualitas mesh. Proses optimalisasi data CAD yang digunakan yaitu Tessellation atau mengkonversi NURBS ke Polygons, berperan untuk menghasilkan output data yang memiliki efisien kinerja dengan topologi serta kualitas mesh yang baik. Hadirnya software 3D Data preparation dan optimasi pada kelas Tessellator. Autodesk Maya merupakan software pemodelan 3D yang mendukung Non-Uniform Rational Basis Spline ataupun CAD memiliki fitur mengkonversi model NURBS ke polygons, pemilihan kebutuhan atau requirement pada tessellation berpengaruh terhadap hasil output. Penilaian dilakukan menggunakan penilaian Objektif menggunakan 3D mesh visual quality metrics berbasis vertex-position Hausdorff Distance sehingga didapatkan requirement pada Tessellation yang efektif. Hasil dari konversi memiliki topologi yang serupa dengan software khusus data preparation dan optimasi, sedangkan hasil penilaian mesh visual quality metrics requirement yang mendekati yaitu menggunakan Tessellation Method Count dan General. Kata Kunci— Tessellation, Mesh Visual Quality, CAD, Polygon In automotive industry, cost of prototyping increases directly with complexity and dependencies of vehicle. As an alternative to physical prototyping can utilize new technologies such as Augmented Reality (AR) and Virtual Reality (VR) are used. And involves the real-time rendering of CAD data which consumes a lot of memory and reduces application performance. Data preparation has an important role to improve performance while maintaining topology and mesh quality. Process of optimizing CAD data used is Tessellation or converting NURBS to Polygons, whose role is to produce output data that has an efficient performance with topology and good mesh quality. Autodesk Maya is a 3D modeling software that supports Non-Uniform Rational Base Spline or CAD which has the feature of converting NURBS models to polygons, the selection of requirements or requirements on tessellation influences the output results. The assessment is done using objective assessment with 3D mesh visual quality metrics based on Hausdorff Distance vertex-position so that the requirements for effective Tessellation are obtained. The results of the conversion have a topology similar to special data preparation and optimization software, while the results of the mesh visual quality metrics requirement approach are close to using the Count and General Tessellation method. Keywords— Tessellation, Mesh Visual Quality, CAD, Polygon


2021 ◽  
pp. 83-91
Author(s):  
Богдан Віталійович Коваленко ◽  
Володимир Васильович Лукін

The subject of the article is to analyze the effectiveness of lossy image compression using a BPG encoder using visual metrics as a quality criterion. The aim is to confirm the existence of an operating point for images of varying complexity for visual quality metrics. The objectives of the paper are the following: to analyze for a set of images of varying complexity, where images are distorted by additive white Gaussian noise with different variance values, build and analyze dependencies for visual image quality metrics, provide recommendations on the choice of parameters for compression in the vicinity of the operating point. The methods used are the following: methods of mathematical statistics; methods of digital image processing. The following results were obtained. Dependencies of visual quality metrics for images of various degrees of complexity affected by noise with variance equal to 64, 100, and 196. It can be seen from the constructed dependence that a working point is present for images of medium and low complexity for both the PSNR-HVS-M and MS-SSIM metrics. Recommendations are given for choosing a parameter for compression based on the obtained dependencies. Conclusions. Scientific novelty of the obtained results is the following: for a new compression method using Better Portable Graphics (BPG), research has been conducted and the existence of an operating point for visual quality metrics has been proven, previously such studies were conducted only for the PSNR metric.The test images were distorted by additive white Gaussian noise and then compressed using the methods implemented in the BPG encoder. The images were compressed with different values of the Q parameter, which made it possible to estimate the image compression quality at different values of compression ratio. The resulting data made it possible to visualize the dependence of the visual image quality metric on the Q parameter. Based on the obtained dependencies, it can be concluded that the operating point is present both for the PSNR-HVS-M metric and for the MS-SSIM for images of medium and low complexity, it is also worth noting that, especially clearly, the operating point is noticeable at large noise variance values. As a recommendation, a formula is presented for calculating the value of the compression control parameter (for the case with the BPG encoder, it is the Q parameter) for images distorted by noise with variance varying within a wide range, on the assumption that the noise variance is a priori known or estimated with high accuracy.


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