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

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...
Probability Histograms01:17

Probability Histograms

A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.
Downsampling01:20

Downsampling

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...
Relative Frequency Histogram01:14

Relative Frequency Histogram

The relative frequency depicts the proportion of data points that have each value. The frequency tells the number of data points that have each value. Like the histogram, a relative frequency histogram also has the same shape with a horizontal scale (the x-axis), but the vertical scale (the y-axis) is marked with relative frequencies (percentages of the whole) instead of actual frequencies. A relative frequency histogram is a graphical representation of a frequency distribution where the...
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
Censoring Survival Data01:09

Censoring Survival Data

Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different reasons...

You might also read

Related Articles

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

Sort by
Same author

Where Machine Learning Fails in Predicting Emerging Contaminant Adsorption: A Decision-Oriented Framework for Model Credibility and Transferability.

Environmental science & technology·2026
Same author

Clinically actionable classification tool for childhood and adult atopic dermatitis via explainable AI: a retrospective cross-sectional study optimizing diagnostic accuracy.

BioData mining·2026
Same author

Improving Kinetic Prediction and Structural-Electronic Mechanistic Coherence in the Fenton Process via a Cross-Scale Machine-Learning Framework.

Environmental science & technology·2026
Same author

MXene membrane with directionally functionalized channel entrances for enhanced ion selectivity and permeability.

Nature communications·2026
Same author

Sanyin decoction alleviates psoriasis by reshaping gut microbiota and modulating the gut-spleen-skin axis.

Frontiers in microbiology·2026
Same author

A prospective, randomized, double-blind, placebo-controlled, multicenter study of thiamin plus folic acid in the treatment of cognitive impairment in patients undergoing maintenance hemodialysis.

Renal failure·2026
Same journal

Change-Prior-Guided Unsupervised Change Detection of Heterogeneous Remote Sensing Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

AgonicDreamer: Enhancing Multi-View Consistency in Text-to-3D Generation via Rectified Score Distillation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

BiCM-Prompt: Bidirectional Cross-Modal Prompt Tuning for Class-Incremental Learning on Multisource Remote Sensing Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

GoP-based Quality Enhancement on Video Compression.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Align then Tensorize: Multi-Level Consistent Anchor Graph Learning for Scalable Multi-View Clustering.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Beyond Fidelity: Diverse Image Synthesis via Retrieval-Augmented Diffusion.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
See all related articles

Related Experiment Video

Updated: May 12, 2026

Lensless Fluorescent Microscopy on a Chip
11:23

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

Recursive histogram modification: establishing equivalency between reversible data hiding and lossless data

Weiming Zhang1, Xiaocheng Hu, Xiaolong Li

  • 1School of Information Science and Technology, University of Science and Technology of China, Hefei 230026, China. weimingzhang@yahoo.cn

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|April 18, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a novel histogram modification method for reversible data hiding (RDH) that leverages entropy coding. This approach achieves near-optimal performance, equating RDH with lossless data compression for improved image security.

More Related Videos

Generating Strictly Controlled Stimuli for Figure Recognition Experiments
05:39

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

Related Experiment Videos

Last Updated: May 12, 2026

Lensless Fluorescent Microscopy on a Chip
11:23

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

Generating Strictly Controlled Stimuli for Figure Recognition Experiments
05:39

Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

Area of Science:

  • Computer Science
  • Information Security
  • Digital Image Processing

Background:

  • Reversible data hiding (RDH) schemes typically involve histogram manipulation for message embedding.
  • Existing methods like difference expansion and histogram shift are effective but have limitations.

Purpose of the Study:

  • To propose a new histogram modification method for RDH.
  • To enhance the performance of existing RDH schemes by focusing on the message embedding stage.

Main Methods:

  • A novel histogram modification technique for RDH is proposed.
  • The method recursively utilizes the decompression and compression processes of an entropy coder for message embedding.
  • The approach is theoretically analyzed for independent identically distributed (i.i.d.) gray-scale host signals.

Main Results:

  • The proposed method asymptotically approaches the rate-distortion bound of RDH under ideal compression conditions.
  • The method establishes an equivalency between reversible data hiding and lossless data compression.
  • Experimental results demonstrate performance improvements over previous RDH schemes, especially for larger images.

Conclusions:

  • The proposed entropy-coder-based histogram modification is a significant advancement in RDH.
  • This method offers a pathway to achieve optimal RDH performance by linking it to the efficiency of lossless compression.
  • The technique shows practical utility and scalability for enhancing image data security.