Jove
Visualize
Contact Us

Related Experiment Videos

Transform-based image enhancement algorithms with performance measure.

S S Agaian1, K Panetta, A M Grigoryan

  • 1Division of Engineering, The University of Texas, San Antonio, TX 78249-0669, USA. sagaian@voyager1.eng.utsa.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 6, 2008
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

Introduction to Scalers01:21

Introduction to Scalers

Many familiar physical quantities can be specified completely by giving a single number and the appropriate unit. For example, "a class period lasts 50 min," or "the gas tank in my car holds 65 L," or "the distance between the two posts is 100 m." A physical quantity that can be specified completely in this manner is called a scalar quantity. The word "scalar" is a synonym for "number." Time, mass, distance, length, volume, temperature, and energy are some examples of scalar quantities.
Scalar...
Transformations of Functions III01:20

Transformations of Functions III

Transformations modify the graphical representation of a function without changing its fundamental form. One common transformation is reflection, which flips the graph across a designated axis. When the vertical coordinates of all points are multiplied by the negative one, the entire graph is mirrored over the horizontal axis. This transformation reverses the vertical orientation of peaks and troughs, akin to signal inversion in electrical systems, where a waveform is flipped, but the timing of...

You might also read

Related Articles

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

Sort by
Same author

(n, k, p)-Gray code for image systems.

IEEE transactions on cybernetics·2012
Same author

Cigarette smoking and high-risk HPV DNA as predisposing factors for high-grade cervical intraepithelial neoplasia (CIN) in young Brazilian women.

Acta obstetricia et gynecologica Scandinavica·1998
Same author

Microinvasive carcinoma of the uterine cervix: histological findings on cone specimens related to residual neoplasia on hysterectomy.

Gynecologic oncology·1997
See all related articles
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

This study introduces novel frequency domain algorithms for image enhancement and object detection. A new metric, Enhancement Measure of Enhancement (EME), quantifies performance to select optimal parameters and transforms.

Area of Science:

  • Digital Image Processing
  • Signal Processing
  • Computer Vision

Background:

  • Frequency domain techniques are crucial for signal and image enhancement.
  • Existing methods may lack flexibility in extracting diverse image characteristics.
  • Object detection and visualization often require advanced enhancement algorithms.

Purpose of the Study:

  • To introduce a new class of frequency domain algorithms for signal and image enhancement.
  • To apply these algorithms for improved object detection and visualization.
  • To develop a quantitative method for evaluating enhancement performance.

Main Methods:

  • Development of novel frequency domain algorithms: magnitude reduction, log-magnitude reduction, iterative magnitude, and log-reduction zonal magnitude.

Related Experiment Videos

  • Application of sequency ordered orthogonal transforms (Fourier, Hartley, cosine, Hadamard) with new parametric operators.
  • Introduction of the Enhancement Measure of Enhancement (EME) for parameter and transform selection.

    • Main Results:

    • The proposed algorithms demonstrate effective signal and image enhancement.
    • Varying operator parameters allows extraction of a wide range of image characteristics from a single transform.
    • Experimental results validate the performance of the new enhancement techniques.

    Conclusions:

    • The new frequency domain algorithms offer a flexible and effective approach to image enhancement.
    • The EME metric provides a valuable tool for optimizing enhancement parameters and transform selection.
    • These advancements contribute to improved object detection and visualization in digital images.