A Novel High Frequency Encoding Algorithm for Image Compression

SIDDEQ, Mohammed and RODRIGUES, Marcos (2017). A Novel High Frequency Encoding Algorithm for Image Compression. EURASIP Journal on Advances in Signal Processing, 26.

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Official URL: https://link.springer.com/article/10.1186/s13634-0...
Link to published version:: 10.1186/s13634-017-0461-4

Abstract

In this paper a new method for image compression is proposed whose quality is demonstrated through accurate 3D reconstruction from 2D images. The method is based on the Discrete Cosine Transform (DCT) together with a high frequency minimization encoding algorithm at compression stage and a new concurrent binary search algorithm at decompression stage. The proposed compression method consists of five main steps: (1) Divide the image into blocks and apply DCT to each block; (2) Apply a high frequency minimization method to the AC-coefficients reducing each block by 2/3 resulting in a Minimized Array; (3) Build a look up table of probability data to enable the recovery of the original high frequencies at decompression stage; (4) Apply a delta or differential operator to the list of DC-components; and (5) Apply arithmetic encoding to the outputs of steps (2) and (4). At decompression stage, the look up table and the concurrent binary search algorithm are used to reconstruct all high frequency AC-coefficients while the DC-components are decoded by reversing the arithmetic coding. Finally, the inverse DCT recovers the original image. We tested the technique by compressing and decompressing 2D images including images with structured light patterns for 3D reconstruction. The technique is compared with JPEG and JPEG2000 through 2D and 3D RMSE. Results demonstrate that the proposed compression method is perceptually superior to JPEG with equivalent quality to JPEG2000. Concerning 3D surface reconstruction from images, it is demonstrated that the proposed method is superior to both JPEG and JPEG2000.

Item Type: Article
Research Institute, Centre or Group: Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
Departments: Arts, Computing, Engineering and Sciences > Engineering and Mathematics
Identification Number: 10.1186/s13634-017-0461-4
Depositing User: Marcos Rodrigues
Date Deposited: 29 Mar 2017 09:31
Last Modified: 07 Apr 2017 15:41
URI: http://shura.shu.ac.uk/id/eprint/15443

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