Line 1: Line 1:
[[File:test2.jpeg|thumbnail]]
+
INTRODUCTION:
 +
 
 +
With the advancement of digital photography and development of microelectronics, it has been possible to introduce a larger public to the Digital Camera. More and more people are taking high quality photographs these days and it has been a challenge for companies to enhance the abilities of these cameras. One of the major issues recognized is blurring of an image. The idea of blur correction is to capture the intent of a photographer’s capturing of the image, and make corrections to the actual photograph. A great deal of research has been done on this topic and today, using softwares such as MATLAB and Python, blur detection has become relatively easier and efficient.
 +
 
 +
A major way to work on blur detection is by extracting certain aspects from the original image automatically and modify these using algorithms. One such way to do so is performing Laplacian on a blurred image. How it works is that this operation detects the rapid changes in intensity in a 2-D image.

Revision as of 03:32, 28 November 2016

INTRODUCTION:

With the advancement of digital photography and development of microelectronics, it has been possible to introduce a larger public to the Digital Camera. More and more people are taking high quality photographs these days and it has been a challenge for companies to enhance the abilities of these cameras. One of the major issues recognized is blurring of an image. The idea of blur correction is to capture the intent of a photographer’s capturing of the image, and make corrections to the actual photograph. A great deal of research has been done on this topic and today, using softwares such as MATLAB and Python, blur detection has become relatively easier and efficient.

A major way to work on blur detection is by extracting certain aspects from the original image automatically and modify these using algorithms. One such way to do so is performing Laplacian on a blurred image. How it works is that this operation detects the rapid changes in intensity in a 2-D image.

Alumni Liaison

BSEE 2004, current Ph.D. student researching signal and image processing.

Landis Huffman