Lincoln School of Computer Science

Assessment Item Briefing Document
Title: CMP3752M Parallel Programming,
Assessment Item One, Coursework

Indicative Weighting: 40%
Learning Outcomes:
On successful completion of this assessment item a student will have demonstrated competence
in the following areas:
• [LO1] demonstrate practical skills in applying parallel algorithms for solving computational
problems;
• [LO3] analyse parallel architectures as a means to provide solutions to complex computational
problems.
Requirements
Your task is to develop a digital image enhancement tool which will perform contrast adjustment
using the histogram equalisation algorithm. The algorithm uses a cumulative intensity histogram to
back-project original image intensities resulting in an image of equalised intensities. The algorithm is
described in detail in [1] with the main calculation steps summarised below and in Fig. 1:
- calculate an intensity histogram from the input image (Fig. 1b);
- calculate a cumulative histogram (Fig. 1c);
- normalise and scale the cumulative histogram (Fig. 1d): the cumulative frequencies are
normalised and scaled to represent output image intensities (e.g. from 0-255 for an 8-bit
image);
- back-projection: the normalised cumulative histogram is used as a look-up table (LUT) for
mapping of the original intensities onto the output image. For each output pixel, the algorithm
should use the original intensity level as an index into the LUT and assign the intensity value
stored at that index.
- the output should be an intensity equalised image (Fig. 1e).

Fig. 1 The individual steps of the histogram equalisation procedure.
Due to a potentially large amount of data, all image processing shall be performed on parallel
hardware and implemented by a parallel software component written in OpenCL. You should develop
your own device code (i.e. kernels) which performs the main steps of the algorithm. The steps include
several classic parallel patterns including scan, histogram and map. Your tool should also report


memory transfer, kernel execution and total program execution times for performance assessment. All
host-side image I/O operations (i.e. reading, displaying of images) are not assessed and can be based
on the code provided during the workshop tutorials. You can use all the code and libraries provided
and developed during the workshop sessions, but you must not use any additional and pre-existing
libraries for this purpose.
The basic version of the tool can be based on purely atomic calculations of the intensity and
cumulative histograms, work with 8-bit intensity monochrome images and pre-determined bin size
(i.e. 256). Further credit will be given for additional functionality such as the efficient parallel
implementation of the histogram based on local memory, variable bin size, different parallel variants
of the scan and support for colour images. In such a case, your program should run and display
execution times for different variants of your algorithms. The test images of different size are
provided together with this assessment brief. During the demonstration, you might be asked to
demonstrate your code working on an “unseen” image provided by your instructor. The main
assessment criteria for this task are related to the correctness of the developed parallel algorithms and
the effectiveness of optimisation strategies. The code should be well commented and clearly
structured into functional blocks.
References:
[1] Rafael C. Gonzalez, R.C. and Woods, R.E (2018), Digital Image Processing. Pearson.

Useful Information
This assessment is an individually assessed component. You will be required to demonstrate your
developed code and answer questions related to your submission during a dedicated workshop session
in the computing labs. Only the submitted code will be considered during demonstrations so further
developments occurring after the deadline will not be taken into account. Non-attendance at the
scheduled demonstration session will automatically result in zero mark for this assessment item. The
demonstration date and further details will be provided during lectures. Please make sure you have a
clear understanding of the grading principles for this component as detailed in the accompanying
Criterion Reference Grid. If you are unsure about any aspect of this assessment component, please
seek the advice of a member of the delivery team.

Submission Instructions
The deadline for submission of this work is included in the School Submission dates on Blackboard.

You must make an electronic submission of your work by using the assessment link on Blackboard
for this component. All developed code should be submitted as a single ZIP file. It is important that
you check that your .ZIP file decompresses to a Visual Studio project that can be directly built and
executed on the computers in the computing labs. This will be required during the final demonstration
of your work. Do not include the test images in your submission as these are relatively large! There is
no written report required for this submission.

DO NOT include this briefing document with your submission.