Performed by: Dor Kasif, Or Flisher Instructor: Rolf Hilgendorf Jpeg decompression algorithm implementation using HLS midterm presentation Winter

The Necessity JPEG- standard for compression of digital images. Done by software, takes a lot of system resources. The solution Implementation of the JPEG decompression/compression algorithm on a dedicated hardware.

Implementation on hardware Design of hardware is done by Hardware Description Languages (HDL. VHDL etc…). HDL’s are programmed concurrently, and is problematic for complicated designs. Programming languages (C/C++,JAVA etc..) are easier to comprehend. The solution using HLS (High Level Synthesis), which enables the use of a programming language as the design and synthesis language.

Our objective Developing a decompressor in a programming language (C++), converting it to a Hardware Description Languages (VHDL) Using Vivado HLS, and Implementing it on a FPGA. The decompressed image will then be available for display on screen in RGB format.

Project Goals Implementing the Jpeg decompression algorithm on a FPGA Using HLS. Displaying the decompressed image in a RGB format on screen. Optimize the implementation to reach the optimal performances possible within the performance envelope of the FPGA. Compare the software decompressed picture to the hardware decompressed picture in terms of Structural Similarity Index Metric (SSIM).

RGB format is divided into 3 color channels, each with it’s own matrix sharing the same size (usually). The encoding /decoding algorithm is done for each channel separately. Dividing into 3 channels

The JPEG encoding algorithm. The decoding algorithm is done exactly the same, but in reverse!

Splitting the image into 8X8 images.

And for each 8x8 image:

Subtracting 128

Implementing the encoding/decoding process

Example picture- Lena Input picture Picture after encoding and decompressing

JPEG-DECOMPRESSOR Module (convert from C++ to VHDL using HLS) 27 bits 8x8 decompressed block Encoded picture Hand shake protocol Block diagram Highest Hierarchy JPEG Testbench (in C++)

We use the test bench file,which inputs the encoded image stream of bits into the module file aka the decoder. The test bench is sending a stream of 27 bits to the module each time. The maximum length of the AC/DC Huffman tables is 27 bits. The module constructs a full sub matrix block of size 8x8. The module will announce the completion of the 8x8 sub matrix through a handshake procedure. The image will then be ready for display on screen in RGB format. Block diagram Highest Hierarchy

1.The acquired decompression algorithm wasn't synthesizable. Solution: We applied: Modifying the decoding algorithm,removing the use of non standard library, removing user interface, etc. and modifying the decoding algorithm to work for our currently custom jpeg. Removing any un- synthesizable functions from the main module. Example: exponentiation, string functions etc. Adjusting the decoder and test-bench for 8x8 blocks + handshake protocol. Encountered problems and solutions

Huffman decoding 27 bits DE quantization Inverse DCT and adding value of 128 to the block 8x8 decompressed block Hand shake protocol Building the sub matrix Zig Zag Block diagram Building the sub matrix The module will do this operation for all (640X480)/(8X8)=4800 blocks module

Block diagram Building the sub matrix Buffer (3*27bit size) getACvalue getDCvalue For DC coeff Buffer has less then 27 bits Hand shake protocol the complete matrix Char to int For AC coeff sub matrix buffer

2. Problems with HLS handling static location of variable size array. In “getDC function” and “getAC function”, in order to interpret the input, we need to compare it bit-by-bit to the members of the AC/DC Huffman tables. Each member of the AC/DC Huffman tables has it’s own length of bits, and is stored inside a 2 dimensional matrix. because of the changing size of each member, they are stored in a string format with a Null character. The HLS can’t synthesize this format. Solution: Instead of comparing bit-by-bit, Converting the input from binary to integer, thus storing the AC/DC Huffman tables in integer format. Encountered problems and solutions

The input will be inserted into a buffer. For the matrix DC coefficient, the input will be inserted to the “getDCvalue” and converted to an integer using the function “char_to_int” in order to find the DC coefficient. The same for the AC coefficient and “getACvalue”. The coefficients will be stored inside another buffer. When there are less then 27 bits inside the buffer, the handshake protocol will be activated and the module will ask for another input. When the matrix is complete, the processed image will continue to the Huffman decoding stage. Block diagram Building the sub matrix

The module will then perform on the sub matrix: Decoding of the compressed image using Huffman and Differential decoding De-Zig Zag operation De quantization Inverse DCT and Adding 128 to the image bit map The module sends back the sub matrix block to the test bench where the test bench will assemble the reconstructed image. Block diagram module

3. The DCDT function uses Trigonometric functions which takes a lot of resources in hardware and is a potential bottle neck. Solution :Replacing the use of Trigonometric functions with constant variables, thus eliminating their dependability. 4. problems with HLS handling C++ float point type and multiplication of them. Could not handle it during synthesis do to multiplication of the default float type. Solution: replacing the use of C++ fixed point types with VIVADO HLS fixed point types which are bit accurate. Encountered problems and solutions

Quality Assessment of the image

Image Quality Assessment 1.We will use Similarity Assessment. 2.We chose SSIM,using the original picture as Full Reference. 3.Measures structural similarity between images. 4.Using “Sliding Window” technique of size 8X8. 5.Focuses on what’s appealing to the human eye, based on HVS (Human Visual System).

SSIM equation The SSIM equation is as follows: The overall image quality MSSIM is the average of the SSIM values. SSIM values range are [0,1], where SSIM=1 means full match.

Progress until PDR presentation Acquired a C++ encoding/decoding algorithm. Modified the algorithm -removing the use of non standard library, removing user interface etc. Adjusting the algorithm to process a single color channel. Developing auxiliary Matlab scripts for handling the images. Started Modifying the decoding algorithm for synthesis in HLS. Eliminating the use of Cosine functions in the decoding process.

Progress since PDR presentation Finished modifying the decoding algorithm for synthesis in HLS. Adjusting the decoder and test-bench for 8x8 blocks + handshake protocol. Replacing the use of C++ floating point types with VIVADO HLS fixed point types. Acquired and modifying Matlab script for SSIM computation.

In progress Improving the hardware implementation. Replacing the existing variable types with VIVADO HLS bit- accurate types. Making the algorithm usable for the standard RGB color channel. simulate implementation(VHDL).

Future planning Time assessment-identification of bottle neck. Improving the hardware implementation. Examining the possibility of parallel/pipeline operations. Compare the hardware generated decompressed picture to the software generated decompressed picture in terms of SSIM with minimal difference. Skipping the use of the aux scripts in Matlab.

Gantt chart NumTaskDuration(days)Start dateEnd date 1Replacing the C++ variable types with VIVADO HLS accurate types731- דצמ 07- ינו 2Making the algorithm usable for standard RGB731- דצמ 07- ינו 3 Simulate implementation(VHDL) + time assessment-bottle neck + hardware improvements5407- ינו 02- מרץ 4Skipping the use of Matlab aux scripts723- פבר 02- מרץ

Gantt chart Final A presentation

Resources -source for the encoding/decoding code -jpeg Wikipedia entry -the technion signal and image processing lab-experiment 3 -Stanford university, department of electrical engineering explanation of the Jpeg format. Essay- The JPEG Still Picture Compression Standard-by Gregory K.Wallace and co. -explanation of the Jpeg format. Howard Hughes Medical Institute, and Laboratory,. By Z. Wang, A. C. Bovik, H. R. Sheikh,and E. P. Simoncelli -Matlab script for SSIM computation. Essay-Image Quality Assessment Techniques pn Spatial Domain-by C.Sasi varnan and co.