A Novel Image Compression Algorithm for High Resolution 3D Reconstruction

Siddeq, Mohammed M.; Rodrigues, Marcos

doi:10.1007/s13319-014-0007-6

Cited by 19 publications

(20 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An analysis of 2D image compression and 3D data compression algorithms developed within the GMPR group is presented here from a compression-encryption perspective. We show that the proposed methods provide simultaneous efficient compression-encryption of data for both 2D images and 3D data structures (Siddeq and Rodrigues, 2016;2015a;2015b;2014a;2014b). In Siddeq and Rodrigues (2014b) we proposed a novel 2D image compression method based on high-frequency sub-bands.…”

Section: The Gmpr Compression-encryption Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Information Systems: Secure Access and Storage in the Age of Cloud Computing

Rodrigues¹,

Siddeq²

2016

AJS

View full text Add to dashboard Cite

Given that cloud computing is a remotely accessed service, the connection between provider and customer needs to be adequately protected against all known security risks. In order to ensure this, an open and clear specification of all standards, algorithms and security protocols adopted by the cloud provider is required. In this paper, we review current issues concerned with security threats to cloud computing and present a solution based on our unique patented compression-encryption method. The method provides highly efficient data compression where a unique symmetric key is generated as part of the compression process and is dependent on the characteristics of the data. Without the key, the data cannot be decompressed. We focus on threat prevention by cryptography that, if properly implemented, is virtually impossible to break directly. Our security by design is based on two principles: first, defence in depth, where our proposed design is such that more than one subsystem needs to be violated to get both the data and their key. Second, the principle of least privilege, where the attacker may gain access to only part of a system. The paper highlights the benefits of the solution that include high compression ratios, less bandwidth requirements, faster data transmission and response times, less storage space, and less energy consumption among others.

show abstract

Section: The Gmpr Compression-encryption Methodsmentioning

confidence: 99%

“…We present an algorithmic solution that has been demonstrated for compression of image and 3D data structures (Siddeq and Rodrigues, 2016;2015a;2015b;2014a;2014b). A unique, data-dependent symmetric key is generated as a side effect to the compression method.…”

Section: Introductionmentioning

confidence: 99%

Information Systems: Secure Access and Storage in the Age of Cloud Computing

Rodrigues¹,

Siddeq²

2016

AJS

View full text Add to dashboard Cite

show abstract

“…(8) can later be recovered by estimating the key values for that block [13,20,21]. However, this problem is underdetermined and extra information is required.…”

Section: High-frequency Minimization Algorithmmentioning

confidence: 99%

A novel high-frequency encoding algorithm for image compression

Siddeq

Rodrigues

2017

EURASIP J. Adv. Signal Process.

View full text Add to dashboard Cite

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.

show abstract

“…For this reason, high-frequencies values in this region are quantized. The quantization process in this research depends on the maximum value in each sub-band, as shown by the following equation (Siddeq, 2014b):…”

Section: Two Level Discrete Wavelet Transform (Dwt)mentioning

confidence: 99%

A Novel 2D Image Compression Algorithm Based on Two Levels DWT and DCT Transforms with Enhanced Minimize-Matrix-Size Algorithm for High Resolution Structured Light 3D Surface Reconstruction

Siddeq

Rodrigues

2015

3D Res

Self Cite

View full text Add to dashboard Cite

This document is the author deposited version. You are advised to consult the publisher's version if you wish to cite from it. SIDDEQ, M and RODRIGUES, Marcos (2015). A novel 2D image compression algorithm based on two levels DWT and DCT transforms with enhanced minimizematrix-size algorithm for high resolution structured light 3D surface reconstruction. 3D Research, 6 (3), p. 26. Published version Copyright and re-use policy AbstractImage compression techniques are widely used in 2D and 3D image and video sequences. There are many types of compression techniques and among the most popular are JPEG and JPEG2000. In this research, we introduce a new compression method based on applying a two level Discrete Wavelet Transform (DWT) and a two level Discrete Cosine Transform (DCT) in connection with novel compression steps for high-resolution images. The proposed image compression algorithm consists of 4 steps: 1) Transform an image by a two level DWT followed by a DCT to produce two matrices: DC-and AC-Matrix, or low and high frequency matrix respectively; 2) apply a second level DCT to the DC-Matrix to generate two arrays, namely nonzero-array and zero-array; 3) apply the Minimize-Matrix-Size (MMS) algorithm to the AC-Matrix and to the other high-frequencies generated by the second level DWT; 4) apply arithmetic coding to the output of previous steps. A novel Fast-Match-Search (FMS) decompression algorithm is used to reconstruct all high-frequency matrices. The FMS-algorithm computes all compressed data probabilities by using a table of data, and then using a binary search algorithm for finding decompressed data inside the table. Thereafter, all decoded DC-values with the decoded AC-coefficients are combined into one matrix followed by inverse two level DCT with two level DWT. The technique is tested by compression and reconstruction of 3D surface patches. Additionally, this technique is compared with JPEG and JPEG2000 algorithm through 2D and 3D RMSE following reconstruction. The results demonstrate that the proposed compression method has better visual properties than JPEG and JPEG2000 and is able to more accurately reconstruct surface patches in 3D.

show abstract

A Novel Image Compression Algorithm for High Resolution 3D Reconstruction

Cited by 19 publications

References 6 publications

Information Systems: Secure Access and Storage in the Age of Cloud Computing

Information Systems: Secure Access and Storage in the Age of Cloud Computing

A novel high-frequency encoding algorithm for image compression

A Novel 2D Image Compression Algorithm Based on Two Levels DWT and DCT Transforms with Enhanced Minimize-Matrix-Size Algorithm for High Resolution Structured Light 3D Surface Reconstruction

Contact Info

Product

Resources

About