Quantitative analysis of information loss in digital image compression and reconstruction

Ye, Zhengmao; Mohamadian, Habib; Ye, Yongmao

doi:10.1109/iccsn.2011.6014297

Cited by 2 publications

(3 citation statements)

References 13 publications

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“…Entropy is a measurement of the discord or randomness of a system. In an image, entropy defines the number of bits required to encode image data (Wu et al, 2013;Ye et al, 2007). Hence, the higher the entropy value, the higher the randomness and detail orientation of the image.…”

Section: Entropymentioning

confidence: 99%

How should B2B firms create image content for high social media engagement? A multimodal analysis

Singh

Gandhi

Kar

et al. 2023

IMDS

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PurposeThis study evaluates the effect of the media image content of business to business (B2B) organizations to accelerate social media engagement. It highlights the importance of strategically designing image content for business marketing strategies.Design/methodology/approachThis study designed a computation extensive research model based upon the stimulus-organism-response (SOR) theory using 39,139 Facebook posts of 125 organizations selected from Fortune 500 firms. Attributes from images and text were estimated using deep learning models. Subsequently, inferential analysis was established with ordinary least squares regression. Further machine learning algorithms, like support vector regression, k-nearest neighbour, decision tree and random forest, are used to analyze the significance and robustness of the proposed model for predicting engagement metrics.FindingsThe results indicate that the social media (SM) image content of B2B firms significantly impacts their social media engagement. The visual and linguistic attributes are extracted from the image using deep learning. The distinctive effect of each feature on social media engagement (SME) is empirically verified in this study.Originality/valueThis research presents practical insights formulated by embedding marketing, advertising, image processing and statistical knowledge of SM analytics. The findings of this study provide evidence for the stimulating effect of image content concerning SME. Based on the theoretical implications of this study, marketing and media content practitioners can enhance the efficacy of SM posts in engaging users.

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Section: Entropymentioning

confidence: 99%

How should B2B firms create image content for high social media engagement? A multimodal analysis

Singh

Gandhi

Kar

et al. 2023

IMDS

View full text Add to dashboard Cite

show abstract

“…DFT returns the value of Fourier transform for a set of values in frequency domain which are equally spaced. 2D DFT of f(x,y) in the spatial domain to F(u, v) in the frequency domain is shown in (9), where M samples can be obtained at values of x from 0 to M-1 and N samples can be obtained at values of y from 0 to N-1.…”

Section: B Discrete Fourier Transform (Dft)mentioning

confidence: 99%

“…In fact, there are at least three dominating compression approaches for digital image, such as prevalent discrete wavelet transform, discrete Fourier transform and optimal statistical schemes. In order to further access the merits and drawbacks of these approaches, quantitative metrics are introduced to measure qualities of image compression based on these major approaches [5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Information Loss Determination on Digital Image Compression and Reconstruction Using Qualitative and Quantitative Analysis

Ye¹,

Mohamadian²,

Ye³

2011

JMM

Self Cite

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To effectively utilize the storage capacity, digital image compression has been applied to numerous science and engineering problems. There are two fundamental image compression techniques, either lossless or lossy. The former employs probabilistic models for lossless storage on a basis of statistical redundancy occurred in digital images. However, it has limitation in the compression ratio and bit per pixel ratio. Hence, the latter has also been widely implemented to further improve the storage capacities, covering various fundamental digital image processing approaches. It has been well documented that most lossy compression schemes will provide perfect visual perception under an exceptional compression ratio, among which discrete wavelet transform, discrete Fourier transform and some statistical optimization compression schemes (e.g., principal component analysis and independent component analysis) are the dominant approaches. It is necessary to evaluate these compression and reconstruction schemes objectively in addition to the visual appealing. Using a well defined set of the quantitative metrics from Information Theory, a comparative study on several typical digital image compression and reconstruction schemes will be conducted in this research.

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Quantitative analysis of information loss in digital image compression and reconstruction

Cited by 2 publications

References 13 publications

How should B2B firms create image content for high social media engagement? A multimodal analysis

How should B2B firms create image content for high social media engagement? A multimodal analysis

Information Loss Determination on Digital Image Compression and Reconstruction Using Qualitative and Quantitative Analysis

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