Just like in one-dimensional signals, we are always susceptible to receiving some noise in our images and we generally apply some preprocessing filters to them before we perform our main work on the images. We can consider noise as a random variation of color or brightness information that is not present in the imaged object, which can take place undesirably due to a sensor and circuitry of a digital camera or scanner. This section uses the ideas of low-pass filter kernels to smoothen our images. These filters remove high frequency content, such as edges and noises, although some techniques allow edges not to be blurred. We will cover the four main image filters available in OpenCV: averaging, Gaussian, median filtering, and bilateral filtering.
OpenCV 3.0 Computer Vision with Java
By :
OpenCV 3.0 Computer Vision with Java
By:
Overview of this book
Table of Contents (15 chapters)
OpenCV 3.0 Computer Vision with Java
Credits
About the Author
Acknowledgment
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Setting Up OpenCV for Java
Handling Matrices, Files, Cameras, and GUIs
Image Filters and Morphological Operators
Image Transforms
Object Detection Using Ada Boost and Haar Cascades
Detecting Foreground and Background Regions and Depth with a Kinect Device
OpenCV on the Server Side
Index
Customer Reviews