The type of attacks are Salt and Pepper noising, additive Gaussian noising, median filtering, Gaussian Smoothing, Histogram Equalization and sharpening attacks.
What does HEQ stand for?
HEQ stands for Histogram Equalization (speech recognition)
This definition appears somewhat frequently and is found in the following Acronym Finder categories:
- Information technology (IT) and computers
See other definitions of HEQ
We have 5 other meanings of HEQ in our Acronym Attic
- High Event Product Tour
- Hybrid Extreme Point Tabu Search (algorithm)
- Higher Education Policy Unit (University of Leeds; UK)
- Hydraulic-Electric Power Unit (mobile robots)
- Hierarchical Encoded Path View
- Health Education Quarterly
- High End Quartz (watches)
- High Environmental Quality (environmental management)
- Higher Education Qualifications (UK)
- Hispanic Executive Quarterly (publication)
- History of Education Quarterly
- HoofBeats Equitation Association
- Higher Education Quality Assessment Council (Estonia)
- Higher Education Quality Committee (South Africa)
- Higher Education Quality Council
- Higher Education Quality Council of Ontario (Canada)
- Higher Education: Quality and Employability (UK)
- Higher Education Quality Evaluation Centre (Riga, Latvia)
- Higher Education Qualifications Framework (South African Council on Higher Education; Pretoria, South Africa)
- High-Efficiency Q-Band MMIC Power Amplifier
Samples in periodicals archive:
Global Histogram Equalization (GHE) is one of the popular methods used to enhance the contrast of image.
To investigate the robustness of the algorithm, the watermarked image is attacked by Average and Median Filtering, Gaussian noise addition, JPEG and JPEG 2000 compression, Rotation, Resizing, Cropping and Histogram Equalization attacks.
Brightness, contrast and histogram equalization functionality enhances image quality.
Extended filtering of single images and entire videos, including tracked areas, to perform operations including histogram equalization, levels adjustment, sharpen, blur, and color space adjustments and video stabilization.
Histogram equalization does not introduce new intensities in the image.
The difference between the images is that one image will use histogram equalization to compare it with the other image that hasn't had this effect performed on it.
Average filtering is applied and contrast of the image is enhanced through histogram equalization process.