system architecture

1. SYSTEM ARCHITECTURE:
GPR Modeling
Input Feature Set
Image Regression
HR TrainedImage
InputImage
Interpolated Set
LR Test Image
ExtractedMessage

2. BLOCK DIAGRAM:
Active
Sampling
SENDER
Login
Details
Login
Query
image GPR Model
LR test
Image
HR output
HR Image
Set
Regression
within
Interpolate
d image
set

3. DATA FLOW DIAGRAM:
Pixel Division: If the pixel values are actually vectors rather than scalar values
(e.g. for color images) than the individual components (e.g. red, blue and green
components)are simply divided separately to producethe output value.

4. Pixel Estimation: Pixel Estimation is the process offinding an estimate,
or approximation, which is a value that is usable for some purposeeven if input
data may be incomplete, uncertain, or unstable. The value is nonetheless usable
because it is derived from the best information available.
Optimal Value Transfer:
Gradient Profile Sharpness Model:Edge sharpness metric is extracted as the
eccentricity of gradient profile description models, which considerboth the
gradient magnitude and spatial scattering of gradient profile.
Interpolated Image: An interpolation technique that reduces the visual distortion
caused by the fractional zoom calculation is the bilinear interpolation algorithm,
where the fractional part of the pixel address is used to compute a weighted
average of pixel brightness values over a small neighborhood of pixels in the
sourceimage.
Regression:A measure of the relation between the mean value of one variable
(e.g. output) and corresponding values of other variables (e.g. time and cost).
HR Output: Your art needs to be a 300 dpi (dots per inch) high-resolution jpg,
tif, or eps file. An eps format is common for logos. You may submit an eps image.
Do not submit a pngimage. A “dot”(also known as a “pixel”) describes the
number of discrete points that can be captured by digital cameras.

5. USE CASE DIAGRAM:

6. SEQUENCE DIAGRAM:
Image as input Pixel Estimate GPS Model Interpolated Image Analysis
Getfiles()
Feature Set()
Active Sample()
LRTestImage()
HR image

7. ACTIVITY DIAGRAM:

8. CollaborationDiagram:
Image as
input
Pixel Estimate
Data
GPS Model
Using Subset
1: Getfiles()
2: SetPPMproperties
3: Feature Extract()
Interpolated ImageHR Output
Image
4: LR Test Image()
5: Regression