14-11-2012, 04:38 PM
BLIND ADAPTIVE SAMPLING OF IMAGES
BLIND ADAPTIVE SAMPLING OF IMAGES.ppt (Size: 1.51 MB / Downloads: 41)
ABSTRACT
Adaptive sampling schemes choose different sampling masks for different images.Blind adaptive sampling schemes use the measurements that they obtain to choose the next sample mask.
In this paper we represent two blind adaptive sampling schemes.
The first is general scheme but not restricted to a specific class of sampling functions.It is based on an underlying statistical model for the image,which is updated according to the available measurements.
A second less general but more practical method uses the wavelet decomposition of an image.It estimates the magnitude of the unsampled wavelet coefficients and samples those with larger estimated magnitude first.
INTRODUCTION
An image is an artifact that depicts or records visual perception.
Volatile image: volatile image is one that exists only for short period of time.This may be reflection of an object by mirror,a projection of camera or scene displayed on a cathode ray tube.
Fixed image: also called as hard copy,is one that has been recorded on a material object
Image processing: Any form of signal processing for which the input is an image such as photograph or videoframe.The output of image processing may be image or set of characteristics or parameters of image
IMAGE COMPRESSION:
The Objective of image compression is to reduce irrelevance and redundancy of the image data in order to able to store or transmit data in an efficient form.
Lossless Compression : error free compression
Lossy Compression : error containing compression
Image compression is minimizing the size in bytes of a graphics file without degrading the quality of the image to an unacceptable level. The reduction in file size allows more images to be stored in a given amount of disk or memory space. It also reduces the time required for images to be sent over the Internet or downloaded from Web pages.
PROPOSED SYSTEM
In this project, we present and discuss two blind adaptive sampling schemes. The first is a general scheme not restricted to a specific class of sampling functions. It is based on an underlying statistical model for the image, which is updated according to the available measurements. A second less general but more practical method uses the wavelet decomposition of an image. It estimates the magnitude of the unsampled wavelet coefficients and samples those with larger estimated magnitude first.
Advantages:
1. By using a less optimal basis the error is reduced.
2. This method collects information about the image much more efficient.