# Watermark-JPEG-with-8x8DCT

**Repository Path**: pn_code/Watermark-JPEG-with-8x8DCT

## Basic Information

- **Project Name**: Watermark-JPEG-with-8x8DCT
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-05-30
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# control.py
run `control.py` to start the program
# embed.py
## watermark pro-processing
The watermark pictrue is `fingerprint.jpg`.It will be processed by Median filter, gray scale, black and white binarization.Then we get the picture named `embedfinger.jpg`
## host pro-processing
The host picture is `host.jpg`.It will be processed by RGB-to-YUV,uint8-to-float32.Because we will DCT on the Y dimension which means the value of brightness later,and DCT need float32.
## watermark embeds into the host
+ Divide host into 8x8 blocks.
+ Calculate `the average number` of fingerprint pixels to be stored for each 8x8 block.You can see output `r` is it.
+ Each block on the Y dimension DCT for the airspace change into frequency domain.Then we discuss the operation to 8x8 blocks in frequency + domain.
+ In a 8x8 block, the unit cell,and its symmetric unit cell of the center,become a pair,named r1,r2
+ Each pair of relationships (r1>r2,r1<r2) is used to record the 0-black and 255-white of the fingerprint pixels to be stored.
+ Embed the average number of fingerprint pixels into mid-frequency cell of the 8x8 block.
+ Each 8x8 block on the Y dimension inverse DCT for frequency domain change into the airspace.The finished product is `finishwm0.jpg`(finish0~5.jpg are different intensity of JPEG compression,finishwm0.jpg is best quality,finishwm5.jpg is worst quality.)
# extract.py
Just 8x8 DCT and find embeded location,then sure the average number of pairs' relationship(r1>r2 is 0-black and r1<r2 is 255-white).Constitute Y dimension of original watermark named `0extractfinger.jpg`(0~5)
# evaluate.py
Calculate PSNR and observe products from different JPEG compresstion.