Discrete cosine transform based processing framework for indexing, decomposition and compression of biospeckle data

被引:1
|
作者
Singh, Puneet [1 ]
Chatterjee, Amit [1 ]
Bhatia, Vimal [1 ]
Prakash, Shashi [2 ]
机构
[1] Indian Inst Technol, Signals & Software Grp, Discipline Elect Engn, Indore 453552, India
[2] Devi Ahilya Univ, Photon Lab, Dept Elect & Instrumentat Engn, Inst Engn & Technol, Indore 452001, India
关键词
laser biospeckle; blood coagulation; image processing; discrete cosine transform; sub-band decomposition; image compression; IMAGE COMPRESSION;
D O I
10.1088/1555-6611/ab9021
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Biospeckle analysis is a useful tool for nondestructive characterization of different samples in diverse areas such as agriculture, engineering, biomedical imaging, medicine, and many more. In this paper, we present a single transform based framework to address three major aspects, viz. numerical quantification, sub-band decomposition and compression of biospeckle data. The discrete cosine transform (DCT) has been advantageously used to develop foundation for all three processing paradigms. First, an efficient method for numerical quantification of biospeckle activity using DCT has been developed. The salient features of the proposed strategy include its extreme simplicity, low complexity, and high accuracy. Furthermore, DCT has also been used in conjunction with the traditional processing methods to decompose and analyze the biospeckle activity associated with different sub-bands. The analysis allows isolation of different physiological and biological processes responsible for overall biospeckle behavior inside the specimen. DCT based image compression strategy to efficiently process the biospeckle data is also reported. Compression enables a way to faithfully process the biospeckle images with lower number of reconstruction coefficients and allows efficient storage and transmission. Performance evaluation and comparison of the proposed technique with the existing methods has been performed in both theoretical and experimental domains. To demonstrate practical utility of the proposed processing strategies blood coagulation process has been studied.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] Application of Image Compression Based on Discrete Cosine Transform
    Zhang, Hongmei
    Pei, Zhili
    Zhang, Zhigao
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON LOGISTICS, ENGINEERING, MANAGEMENT AND COMPUTER SCIENCE (LEMCS 2015), 2015, 117 : 1352 - 1355
  • [2] Financial Digital Images Compression Method Based on Discrete Cosine Transform
    Wang, Wenjin
    Lu, Miaomiao
    Dai, Xuanling
    Jiang, Ping
    AUTOMATIC CONTROL AND COMPUTER SCIENCES, 2024, 58 (05) : 592 - 601
  • [3] Fast directional discrete cosine transform for image compression
    Chen, Bo
    Wang, Hongxia
    Cheng, Lizhi
    OPTICAL ENGINEERING, 2010, 49 (02)
  • [4] Image Compression Based on a Partially Rotated Discrete Cosine Transform With a Principal Orientation
    Lee, Gihwan
    Choe, Yoonsik
    IEEE ACCESS, 2021, 9 : 101773 - 101786
  • [5] Research on Compression and Reconstruction of Wind Turbine Vibration Signal Based on Discrete Cosine Transform
    Huang, Zhidong
    Gan, Xiaoye
    ADVANCES IN MANUFACTURING SCIENCE AND ENGINEERING, PTS 1-4, 2013, 712-715 : 1668 - 1671
  • [6] Discrete Cosine Transform Optimization in Image Compression Based on Genetic Algorithm
    Liu Yuan-yuan
    Chen He-xin
    Zhao Yan
    Sun Hong-yan
    2015 8TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING (CISP), 2015, : 199 - 203
  • [7] Image compression based on discrete cosine transform and multistage vector quantization
    Zhou, Xiao
    Bai, Yunhao
    Wang, Chengyou
    International Journal of Multimedia and Ubiquitous Engineering, 2015, 10 (06): : 347 - 356
  • [8] Video compression using frame redundancy elimination and discrete cosine transform coefficient reduction
    Alshehri, Saleh Ali
    MULTIMEDIA TOOLS AND APPLICATIONS, 2021, 80 (01) : 367 - 381
  • [9] A hybrid compression method for the NMR data based on window averaging and Discrete Cosine Transform
    Gu, Mingxuan
    Xie, Ranhong
    Jin, Guowen
    Shao, Liang
    COMPUTERS & GEOSCIENCES, 2021, 157
  • [10] Signal Compression Using the Discrete Wavelet Transform and the Discrete Cosine Transform
    Barsanti, Robert J.
    Athanason, Athanasios
    2013 PROCEEDINGS OF IEEE SOUTHEASTCON, 2013,