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Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
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Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
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In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
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Related Experiment Video

Updated: Oct 12, 2025

Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

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Improved Coefficient Recovery and Its Application for Rewritable Data Embedding.

Alan Sii1, Simying Ong2, KokSheik Wong1

  • 1School of Information Technology, Monash University Malaysia, Subang Jaya 47500, Malaysia.

Journal of Imaging
|November 25, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces an adaptive method for JPEG coefficient recovery, improving efficiency by up to 27% and enhancing image quality. A novel data embedding technique also allows for significant data insertion into images.

Keywords:
DCTadaptivecoefficient recoveryrewritablesegmentation

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Area of Science:

  • Digital Image Processing
  • Data Compression
  • Information Security

Background:

  • JPEG is a widely used image coding standard, but data loss due to errors or damage is a common issue.
  • Existing coefficient recovery methods often rely on inaccurate segmentation assumptions, limiting their effectiveness.
  • Data hiding in images is an active area of research, with a need for efficient and robust methods.

Purpose of the Study:

  • To develop an adaptive coefficient recovery method for JPEG images that overcomes limitations of previous approaches.
  • To propose an improved rewritable adaptive data embedding method that leverages coefficient recoverability.
  • To enhance both the efficiency and image quality of JPEG data recovery and embedding.

Main Methods:

  • An adaptive segmentation technique was employed for more accurate JPEG coefficient recovery.
  • A novel rewritable adaptive data embedding method was developed, selecting DCT patches and blocks based on precision.
  • Performance was evaluated based on CPU time, image quality, and data embedding capacity.

Main Results:

  • The adaptive coefficient recovery method demonstrated up to a 27% improvement in CPU time compared to conventional methods.
  • The proposed method achieved better image quality for most tested images.
  • The data embedding method successfully embedded 20,146 bits into a 512x512 image.

Conclusions:

  • Adaptive coefficient recovery significantly enhances the performance and quality of JPEG error resilience.
  • The proposed data embedding method offers a practical solution for secure and high-capacity information hiding in JPEG images.
  • These advancements contribute to more robust image storage and transmission systems.