Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Histogram01:05

Histogram

12.7K
The histogram is a graphical representation in the x-y form of data distribution in a data set. The horizontal x-axis is labeled with what the data represents (for instance, distance from your home to school). The vertical y-axis is labeled either frequency or relative frequency (or percent frequency or probability).
A histogram graph consists of contiguous (adjoining) boxes. The heights of the bars correspond to frequency values. The graph will have the same shape with respective labels. The...
12.7K
Computed Tomography01:10

Computed Tomography

7.6K
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
7.6K
Downsampling01:20

Downsampling

872
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
872
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

893
DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
893

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Identification of <i>GADD45B</i>, <i>HMGB3</i>, <i>LMNB2</i>, and <i>MFAP5</i> as lactylation-related prognostic markers for survival prediction in esophageal cancer.

Translational cancer research·2026
Same author

Novel Perspective for Prognostic Stratification and Personalized Therapy in Breast Cancer Patients: Development of Cancer Stem Cells and Metabolism-Associated Prognostic Model.

International journal of women's health·2026
Same author

Pulsed-Closure Assisted Continuous Atmospheric Pressure Interface for Miniature Ion Trap Mass Spectrometry with Enhanced Resolution and Sensitivity.

Journal of the American Society for Mass Spectrometry·2026
Same author

Reversible cupping and persistent vessel narrowing after glaucoma surgery in childhood glaucoma: a quantitative fundus photograph study.

Frontiers in medicine·2026
Same author

Epidemiological characteristics and changing patterns of hospitalizations among middle-aged and elderly patients in Northwest China, 2020-2024: A retrospective cohort study.

SAGE open medicine·2026
Same author

Oligomeric ultranano hydrogen water improves flock uniformity, antioxidant capacity and intestinal health in growth phase layer-type chickens.

Poultry science·2026

Related Experiment Video

Updated: May 3, 2026

Clock Scan Protocol for Image Analysis: ImageJ Plugins
07:19

Clock Scan Protocol for Image Analysis: ImageJ Plugins

Published on: June 19, 2017

17.2K

Identification of bitmap compression history: JPEG detection and quantizer estimation.

Zhigang Fan1, Ricardo L de Queiroz

  • 1Xerox Corp., Webster, NY 14580, USA. zfan@crt.xerox.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 2, 2008
PubMed
Summary

This study presents a fast method to detect JPEG compression and estimate its quantization table. This helps in removing compression artifacts and optimizing JPEG re-compression.

More Related Videos

Quantifying the Effects of Antimicrobials on In vitro Biofilm Architecture using COMSTAT Software
06:18

Quantifying the Effects of Antimicrobials on In vitro Biofilm Architecture using COMSTAT Software

Published on: December 14, 2020

3.5K
Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures
07:05

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures

Published on: February 15, 2022

2.0K

Related Experiment Videos

Last Updated: May 3, 2026

Clock Scan Protocol for Image Analysis: ImageJ Plugins
07:19

Clock Scan Protocol for Image Analysis: ImageJ Plugins

Published on: June 19, 2017

17.2K
Quantifying the Effects of Antimicrobials on In vitro Biofilm Architecture using COMSTAT Software
06:18

Quantifying the Effects of Antimicrobials on In vitro Biofilm Architecture using COMSTAT Software

Published on: December 14, 2020

3.5K
Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures
07:05

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures

Published on: February 15, 2022

2.0K

Area of Science:

  • Digital Image Processing
  • Computer Vision
  • Signal Processing

Background:

  • Image processing often requires analyzing images without prior knowledge of compression history.
  • JPEG compression can degrade image quality, necessitating artifact removal or re-compression.
  • Identifying JPEG compression and its parameters is crucial for effective post-processing.

Purpose of the Study:

  • To develop a fast and efficient method for detecting JPEG compression.
  • To estimate the specific quantization table used during JPEG compression.
  • To enable informed image processing tasks like artifact removal and re-compression.

Main Methods:

  • Developing a method to detect a JPEG compression signature within image data.
  • Implementing a maximum likelihood estimation technique to determine JPEG quantization steps.
  • Analyzing image data for characteristic compression artifacts.

Main Results:

  • A robust method for accurately detecting prior JPEG compression.
  • Successful estimation of JPEG quantization steps with high accuracy.
  • The developed method is efficient and fast for practical applications.

Conclusions:

  • The proposed method reliably identifies JPEG compressed images and their quantization tables.
  • This capability is essential for advanced image processing tasks involving JPEG files.
  • The technique offers a robust solution for understanding and mitigating JPEG compression effects.