Assessment Of Grayscale Image in Terms of Texture Quality Using Reference Image

被引:0
作者
Aghamiri, Hamid Reza [1 ]
Ghassemian, Hassan [1 ]
机构
[1] Tarbiat Modares Univ, Fac Elect & Comp Engn, Tehran, Iran
来源
2016 EIGHTH INTERNATIONAL CONFERENCE ON INFORMATION AND KNOWLEDGE TECHNOLOGY (IKT) | 2016年
关键词
image quality assessment(IQA); texture; local ternary pattern(LTP);
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Texture is one of the most important image's features, which has an important role in some image-processing applications such as segmentation and classification. The main problem is to obtain how much textures are reminded from reference image in the distorted image. To solve this problem image quality, assessment (IQA) plays main role and compares the amount of difference of texture between both images. This paper proposed a novel method to assess fully reference (FR) texture quality assessment, which is more sensible and sensitive to pixel arrangements. The grayscale images used for our experiments are BRODATZ imagery. The experimental results show superiority of proposed method compared to some popular texture assessment methods.
引用
收藏
页码:144 / 148
页数:5
相关论文
共 50 条
  • [1] Automated Clustering Of Histology Slide Texture Using Co-Occurrence Based Grayscale Image Features and Manifold Learning
    Onder, Devrim
    Karacali, Bilge
    BIYOMUT: 2009 14TH NATIONAL BIOMEDICAL ENGINEERING MEETING, 2009, : 365 - 368
  • [2] Image Block Matching Based on GLCM (Gray level Co-occurence Matrix) Texture Feature on Grayscale Image Auto Coloring
    Sipan, Muhammad
    Susiki, Supeno Mardi N.
    Yuniarno, Eko Mulyanto
    2017 INTERNATIONAL SEMINAR ON INTELLIGENT TECHNOLOGY AND ITS APPLICATIONS (ISITIA), 2017, : 302 - 306
  • [3] Detection of static objects in an image using texture analysis
    Jabloncik, Frantisek
    Hargas, Libor
    Koniar, Dusan
    Volak, Jozef
    13TH INTERNATIONAL SCIENTIFIC CONFERENCE ON SUSTAINABLE, MODERN AND SAFE TRANSPORT (TRANSCOM 2019), 2019, 40 : 265 - 270
  • [4] UNSUPERVISED IMAGE COMPRESSION USING GRAPHCUT TEXTURE SYNTHESIS
    Ierodiaconou, Stephen
    Byrne, James
    Bull, David R.
    Redmill, David
    Hill, Paul
    2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6, 2009, : 2289 - 2292
  • [5] Detection of the flood boundary in SAR image using texture
    Han, CM
    Guo, HD
    Shao, Y
    Liao, JJ
    IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium, Vols 1-8, Proceedings, 2005, : 3697 - 3699
  • [6] Pipelined Technique for Image Retrieval Using Texture and Color
    Srivastava, Divya
    Goel, Surbhi
    Agarwal, Suneeta
    2017 4TH INTERNATIONAL CONFERENCE ON POWER, CONTROL & EMBEDDED SYSTEMS (ICPCES), 2017,
  • [7] METHOD FOR TEXTURE CLASSIFICATION USING IMAGE STRUCTURAL FEATURES
    Asatryan, D. G.
    Kurkchiyan, V. V.
    Kharatyan, L. R.
    COMPUTER OPTICS, 2014, 38 (03) : 574 - 579
  • [8] Texture synthesis quality assessment using perceptual texture similarity
    Dong, Xinghui
    Zhou, Huiyu
    KNOWLEDGE-BASED SYSTEMS, 2020, 194
  • [9] Medical image segmentation using texture directional features
    Mavromatis, S
    Boï, JM
    Sequeira, J
    PROCEEDINGS OF THE 23RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4: BUILDING NEW BRIDGES AT THE FRONTIERS OF ENGINEERING AND MEDICINE, 2001, 23 : 2673 - 2676
  • [10] Texture image classification using multi fractal dimension
    LIU Zhuo-fu and SANG En-fang School of Underwater Acoustic Engineering
    JournalofMarineScienceandApplication, 2003, (02) : 76 - 81