A hybrid image compression technique based on DWT and DCT transforms

Benchikh, Salam; Corinthios, M.J.

doi:10.1049/cp.2011.1065

Cited by 28 publications

(10 citation statements)

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“…In JPEG compression method a standard 8 × 8 quantization matrix Q is used to multiply the resultant coefficient matrix. The Q matrix considered here is one used in the standard JPEG compression algorithm [6]. A quantization parameter qp is also used to multiply the Q matrix before the quantization process.…”

Section: 1mentioning

confidence: 99%

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Improved transform based image compression methods

Al-Fayadh¹,

Abdulkareem²

2017

ams

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A Modified Discrete Wavelet Transform (DWT) and Hybrid image compression methods which use integral transformations are introduced in this paper. Discrete Cosine Transform (DCT) as implemented in the standard JPEG compression and DWT for its useful multiresolution properties are used first. A Modified DWT method with variable thresholds used to discard some coefficients is suggested. A mathematical model consisting of the proposed Hybrid Method that takes advantage of both the DCT and Modified DWT is then introduced. A new approach to truncate transform coefficients is followed in the proposed method to obtain wide range of bit rates in bits per pixel (bpp). The Modified DWT and proposed Hybrid compression methods are compared to the JPEG and JPEG2000 compression standards. The performances of the suggested methods show clear improvement (about 7dB) in Peak Signal-to-Noise Ratio and better Mean Structural Similarity (MSSIM) of the decompressed image (about 22%) compared to the standard JPEG2000 method when operating at the same bit rate.

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Section: 1mentioning

confidence: 99%

“…Since 2000 many efforts have been introduced to use Hybrid compression methods ( [1], [2], [3], [4], [5], [6], [16], [18], [19]). Improved performance has been shown by these methods in term of compression ratio with reasonable peak-signal -tonoise ratio (PSNR).…”

Section: Introductionmentioning

confidence: 99%

Improved transform based image compression methods

Al-Fayadh¹,

Abdulkareem²

2017

ams

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“…So it is known as lossy compression. It is used in mathematics for solving fractional differential equations, JPEG standard [8].…”

Section: Discrete Cosine Transform (Dct)mentioning

confidence: 99%

“…Benchikh and Corinthios [8] discussed the combination of two strategies Discrete Wavelet Transform and Discrete Cosine Transform for image compression. In this method they compared their methods with DCT compression technique and DWT compression technique.…”

Section: Iirelated Workmentioning

confidence: 99%

Image Compression Using Decision Tree Technique

Kaur¹

2017

ijarcs

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Image compression is the process of minimizing the size of file without degrading the file quality. The reduction in file size permits number of files to be stored in a memory space. The proposed compression method used the decision tree algorithm for compression of a grey scale images. The Decision tree reads an image which needs to compress. Patches are created and assign weight to each patch on the basis of similarity between patches. Decision tree is formed based on the similarity between the pixels. Then data is merged to form compressed image otherwise define root node which has maximum weight, left node which has less weight than root node and right node which has minimum weight and decision tree is created. The proposed method is evaluated using the Image Quality Measures (IQM) like Peak-Signal to Noise Ratio (PSNR), Compression Ratio (CR), Mean Square Error (MSE) and Elapsed Time (ET). The experimental results of the proposed method are compared with Huffman method and Wavelet Difference Reduction method. From the experimental results it has been concluded that the proposed method is better than Huffman method and Wavelet Difference Reduction.

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“…Combining DCT and DWT was done in References 8,9 by applying the DCT on the discrete wavelet transform coefficients. In Reference 10 , hybrid matrices are generated using combination of various matrices like DCT, Hadamard, and Kekre's Transform.…”

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Combined DCT‐Haar transforms for image compression

Dagher

Saliba

Farah

2018

Int J Imaging Syst Tech

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Discrete Cosine Transform and Haar wavelet transform are very important transforms in image compression. The objective of this paper is to combine the advantages of these 2 transforms into one transform in order to get better peak-signal-tonoise-ratio (PSNR) and keeping good compression ratio. Our first approach was to apply separately on each 8x8 block the Haar and the DCT transforms. A signaling bit along the transform which gave better PSNR are quantized and transmitted. Our second approach was to construct a new hybrid transform which is a combination of these 2 transforms. We mixed both DCT and Haar transforms into one transform. Results show that our approach outperforms the existing DCT and Haar methods giving a higher PSNR than DCT for the same compression ratio, and permitting better edge recovery than the Haar transform. K E Y W O R D S discrete cosine transform, Haar, hybrid, image compression, wavelet

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A hybrid image compression technique based on DWT and DCT transforms

Cited by 28 publications

References 0 publications

Improved transform based image compression methods

Improved transform based image compression methods

Image Compression Using Decision Tree Technique

Combined DCT‐Haar transforms for image compression

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