@article{MAKHILLJEAS201914817665,
    title = {A Novel Lossless Image Compression Technique Based on
Firefly Optimization Algorithm},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {14},
    number = {8},
    pages = {2642-2647},
    year = {2019},
    issn = {1816-949x},
    doi = {jeasci.2019.2642.2647},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2019.2642.2647},
    author = {Abdulrahman and},
    keywords = {Image compression,lossless,SIFT,MSA,pixels,validate},
    abstract = {Image compression still remains a hot research topic due to the generation of massive amount data
which needs to be stored or transmitted. Numerous approaches have been presented for image compression
to represent the images in a compacted form with no repeated or unrelated pixels. Presently, evolutionary
algorithms become more popular to solve the real world problems in an efficient manner. In this study,
Firefly (FF) optimization algorithm based on Discrete Cosine Transformation (DCT) is introduced to determine
the best fitness value for all DCT block. When the fitness values are computed for DCT blocks, compression
process takes place. To enhance the overall compression performance, image warping process is also used as
a preprocessing step. However, Space Invariant Feature Transform (SIFT) matching procedure is employed to
validate the difference between reference and reconstructed image. A detailed comparison study is performed
between the proposed Firefly (FF) algorithm and existing Pollination Based Optimization (PBO) using a set of
benchmark images. The proposed method is successfully applied and the experimental analysis prove that the
presented FF method is found to be better than previous methods in terms of various performance measures
like Compression Ratio (CR), Compression Time (CT), Peak Signal to Noise Ratio (PSNR), Mean Square Error
(MSE) and Structural Similarity Index (SSIM).}
    }