Purdue University Graduate School
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Lossless Color Image Compression with Bit-Error Awareness

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posted on 2019-12-10, 20:25 authored by Xuan PengXuan Peng

Image compression is widely applied to medical imaging, remote sensing applications, biomedical diagnosis, multimedia applications and so on [1]-[4]. In many cases, considering the factor of image quality, we use a lossless compression method to compress the image.

In this thesis work, we propose bit-error aware lossless compression algorithms for color image compression subject to bit-error rate during transmission. Each of our proposed algorithms includes three stages. The first stage is to convert the RGB images to YCrCb images, and the second stage predicts the transformed images to generate the residue sequences. Optimization algorithms are used to search the best combination of the image conversion and prediction. At the last stage, the generated residue sequences are encoded by several residue coding algorithms, which are 2-D and 1-D bi-level block coding, interval Huffman coding and standard Huffman coding algorithms. Key parameters, such as color transformation information, predictor parameters and residue coding parameters, are protected by using (7,4) Hamming code during image transmission,

The compression ratio (CR) and peak signal to noise ratio (PSNR) are two significant performance indicators which are used to evaluate the experimental results. According to the experimental results, the 2-D bi-level block coding algorithm is verified as the best coding method.


Degree Type

  • Master of Science in Electrical and Computer Engineering


  • Electrical and Computer Engineering

Campus location

  • Hammond

Advisor/Supervisor/Committee Chair

Li-zhe Tan

Additional Committee Member 2

Xiaoli Yang

Additional Committee Member 3

Quamar Niyaz