An efficient color image compression technique

Abd-Elhafiez, Walaa M.; Gharibi, Wajeb; Heshmat, Mohamed

doi:10.12928/telkomnika.v18i5.8632

Cited by 9 publications

(12 citation statements)

References 17 publications

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“…Here, we include the outcoms of the some existed emthods and the same sample. To demonstrate our technology used in this work, we used sound test sample in the researches [17,26,30]. In AMBTC format, the sample is a compressed wave file format.…”

Section: Resultsmentioning

confidence: 99%

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Adaptive speech compression based on AMBTC

Salih¹

2022

PEN

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Most of the AMBTC-based RDH (absolute instantaneous block truncation) schemes Cannot be decrypted because AMBTC, which is unknown to most device. Also, some of the RDH methods based on AMBTC. But the load capacity obtained is low. For this purpose, in this work, a scalable RDH scheme based on AMBTC was introduced from the AMBTC zip code. In contrast to the decoder-based AMBTC-based RDH methods that are only able to achieve a constant payload for adjust the audio. Due to its advantages, sound pressure has attracted a great deal of attention in the last 20 years. The main developments concern transmission requirements and storage capacity. The need for high-quality audio data has been increased due to sudden improvements in computer manufacturers and technologies. Therefore, the developments include speech compression technologies, in which the two compression classes are lossless. This paper aims to review techniques for specification compression methods using AMBTC (a momentary absolute block truncation notation based ) method, and to summarize their importance and uses.

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Section: Resultsmentioning

confidence: 99%

“…The only way to overcome this situation is to compress the information signal by removing its excess. The pressure ratio can be easily changed with waves while other methods have fixed pressure ratios [16,17]. Othman or Khalifa, Syring Habib Harding and Aisha Hassan description in order of importance of sound pressure.…”

Section: Literature Reviewmentioning

confidence: 99%

Adaptive speech compression based on AMBTC

Salih¹

2022

PEN

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“…[ 26 ] CR is a dimensional comparison between the original image and the compressed image. [ 27 ] Accuracy is a comparison between the original image and the classified image.…”

Section: Proposed Texture Extractionmentioning

confidence: 99%

A Novel Texture Extraction-Based Compressive Sensing for Lung Cancer Classification

Irawati

Hadiyoso

Budiman

et al. 2022

Journal of Medical Signals &Amp; Sensors

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Background: Lung cancer images require large memory storage and transmission bandwidth for sending the data. Compressive sensing (CS), as a method with a statistical approach in signal sampling, provides different output patterns based on information sources. Thus, it can be considered that CS can be used for feature extraction of compressed information. Methods: In this study, we proposed a novel texture extraction-based CS for lung cancer classification. We classify three types of lung cancer, including adenocarcinoma (ACA), squamous cell carcinoma (SCC), and benign lung cancer (N). The classification is carried out based on texture extraction, which is processed in 2 stages, the first stage to detect N and the second to detect ACA and SCC. Results: The simulation results show that two-stage texture extraction can improve accuracy by an average of 84%. The proposed system is expected to be decision support in assisting clinical diagnosis. In terms of technical storage, this system can save memory resources. Conclusions: The proposed two-step texture extraction system combined with CS and K- Nearest Neighbor has succeeded in classifying lung cancer with high accuracy; the system can also save memory storage. It is necessary to examine the complexity of the proposed method so that it can be analyzed further.

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“…Speech compression is a procedure that purposes to change the human speech in a coded frame so that it can be reestablished as the original signal to decrease the redundancy between neighboring samples and between the adjoining frames [3]. The idea of audio compression is to take up lower capacity space to lower transfer speed for transmission by implementing encodes audio data so that various compression methods have been prepared to apply this objective [4,5]. It is possible to classify audio compression into two groups such as every other digital data compression; these groups are lossless compression and lossy compression [6].…”

Section: Introductionmentioning

confidence: 99%

Audio compression using transforms and high order entropy encoding

Ahmed

George

Hadi

2021

IJECE

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<span>Digital audio is required to transmit large sizes of audio information through the most common communication systems; in turn this leads to more challenges in both storage and archieving. In this paper, an efficient audio compressive scheme is proposed, it depends on combined transform coding scheme; it is consist of i) bi-orthogonal (tab 9/7) wavelet transform to decompose the audio signal into low & multi high sub-bands, ii) then the produced sub-bands passed through DCT to de-correlate the signal, iii) the product of the combined transform stage is passed through progressive hierarchical quantization, then traditional run-length encoding (RLE), iv) and finally LZW coding to generate the output mate bitstream. The measures Peak signal-to-noise ratio (PSNR) and compression ratio (CR) were used to conduct a comparative analysis for the performance of the whole system. Many audio test samples were utilized to test the performance behavior; the used samples have various sizes and vary in features. The simulation results appear the efficiency of these combined transforms when using LZW within the domain of data compression. The compression results are encouraging and show a remarkable reduction in audio file size with good fidelity.</span>

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An efficient color image compression technique

Cited by 9 publications

References 17 publications

Adaptive speech compression based on AMBTC

Adaptive speech compression based on AMBTC

A Novel Texture Extraction-Based Compressive Sensing for Lung Cancer Classification

Audio compression using transforms and high order entropy encoding

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