• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to project page

2016 Fiscal Year Final Research Report

Learning-Based Design and Implementation of Non-separable Oversampled Lapped Transforms for Multidimensional Signal Restoration

Research Project

  • PDF
Project/Area Number 26420347
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Communication/Network engineering
Research InstitutionNiigata University

Principal Investigator

Muramatsu Shogo  新潟大学, 自然科学系, 准教授 (30295472)

Project Period (FY) 2014-04-01 – 2017-03-31
Keywords冗長変換 / スパース表現 / ボリュームデータ復元 / 辞書学習 / GPGPU実装 / 確率的勾配降下法 / タイトフレーム / 画像処理
Outline of Final Research Achievements

In this project, we proposed a multidimensional transform with the redundant, non-separable, overlapped, symmetric, compact-supported and tight property. We also conducted the theoretical analysis, design, implementation, and application development. First, we extended the existing non-separable lapped orthogonal transform to redundant configuration and clarify its properties. As well, we proposed an example-based learning design method and showed its effectiveness. In addition, we showed the possibility of real-time processing through GPGPU/FPGA implementation. Besides, it was applied to image/volumetric data restoration and validity was confirmed. We also extended the proposed transform to complex coefficient type as preparation for application development to complex image restoration processing.

Free Research Field

信号処理

URL: 

Published: 2018-03-22  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi