<p>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.</p>
<p>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, <a>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</a>. Key parameters, such as color transformation
information, predictor parameters and residue coding parameters, are protected by
using (7,4) Hamming code during image transmission, </p>
<p><a>The
compression ratio (CR) and peak signal to noise ratio (PSNR)</a>
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.</p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/11342405 |
| Date | 10 December 2019 |
| Creators | Xuan Peng (8101316) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/Lossless_Color_Image_Compression_with_Bit-Error_Awareness/11342405 |
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