Developed JPEG Algorithm Applied in Image Compression

Hussain, Abdullah A.; Al-Khafaji, Ghadah; Siddeq, Mohammed M.

doi:10.1088/1757-899x/928/3/032006

Cited by 9 publications

(3 citation statements)

References 10 publications

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“…We chose to use the JPEG technique in our research because it also utilizes DCT, which we utilized in our own approach. Our comparison is based on achieving a higher compression ratio while maintaining good visual quality [11,17].…”

Section: Comparison Our Proposed Methods With Jpeg and Jpeg2000 Techn...mentioning

confidence: 99%

The multi-quantization process with matrix size reduction is applied to compress images with strip structure light that is commonly used in 3D reconstructions

Abdulrazzaq

Rasheed

Siddeq

2023

Preprint

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In this paper, a novel method for 2D image compression is proposed and demonstrated through high-quality image reconstruction with compression ratios up to 99%. The proposed algorithm uses multiple divisions to divide an image into two different matrices: the number of division matrix and the reminder matrix. DCT is applied to these matrices to increase high-frequency coefficients. Then, the final coefficient matrices are encoded using Binary Matrix encoding Algorithm. This final new algorithm removes blocks of zeros and indexes them with only a “0”, while other blocks with nonzero coefficients are kept. At the decompression stage, the process starts with inverse Binary Matrix encoding, which returns all zeros at exact locations. The next step is inverse DCT, which is applied to retrieve the original matrices: the Number of Division matrix and the Reminder matrix. Finally, the image is decoded by combining the two retrieved matrices. The experimental results show that our method achieved high compression ratios up to 99% with better perceptual quality of reconstructed images compared to the popular JPEG method.

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Section: Comparison Our Proposed Methods With Jpeg and Jpeg2000 Techn...mentioning

confidence: 99%

The multi-quantization process with matrix size reduction is applied to compress images with strip structure light that is commonly used in 3D reconstructions

Abdulrazzaq

Rasheed

Siddeq

2023

Preprint

Self Cite

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“…Differential Pulse Code Modulation (DPCM): DPCM means to predict the next coefficient value based on the previous coefficient value and then encode the difference between the predicted value and the actual value. This article only uses DPCM; to a 0 , decrease the number of bits desires to perform it by executing the following equation [25][26][27]:…”

Section: Encoding Of a 0 A 1 A 2 Coefficientsmentioning

confidence: 99%

Image Signal Decomposition Using Polynomial Representation with Hybrid Lossy and Non-Lossy Coding Scheme

Ahmed

George

Hadi

2022

Iraqi Journal of Science

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This article presents a polynomial-based image compression scheme, which consists of using the color model (YUV) to represent color contents and using two-dimensional polynomial coding (first-order) with variable block size according to correlation between neighbor pixels. The residual part of the polynomial for all bands is analyzed into two parts, most important (big) part, and least important (small) parts. Due to the significant subjective importance of the big group; lossless compression (based on Run-Length spatial coding) is used to represent it. Furthermore, a lossy compression system scheme is utilized to approximately represent the small group; it is based on an error-limited adaptive coding system and using the transform coding scheme (discrete cosine transform or bi-orthogonal transform). Experimentally, the developed system has achieved high compression ratios with acceptable quality for color images. The performance results are comparable to those introduced in recent studies; the accomplishment of the introduced image compression system was analyzed and compared with the performance of the JPEG standard. The results of the developed system show better performance than that of the JPEG standard.

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“…However, a significant issue arises due to the large file sizes associated with these images, which can impact device storage and network bandwidth (Salman and Rafea, 2020;Shihab, 2023;Mohammed et al, 2021). Image compression systems aim to address this problem by efficiently preserving image information while eliminating unnecessary redundancy found among neighboring pixels (Abouali, 2013; Ahmed et al, 2020;Hussain et al, 2020;Mahdi and Al-khafaji, 2022). In addition, using Internet applications has become necessary, meaningful, and indispensable, as most things are currently managed via the Internet.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Pixel-Based Technique for Grayscale Image Compression

Abed,

AL-Khafaji

2024

jcoeng

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Grayscale images are extensively used due to their simplicity and cheapness in storage and transmission compared to color one of RGB base. It can also be considered a solution for color-blind people to ensure a better view of things and reading. However, unfortunately, it is still quite overburdened with redundancy(s) in which the data compression exploits them efficiently depending on the type and way of redundancy removal. This work introduces a hybrid compression system to compress grayscale images using the adaptive pixel-based technique (PBT) of optimized modeling base, with incorporated Minimize Matrix Size Algorithm (MMSA) of three digits values (C321) to encode the residual compactly along the need to overhead information (index, mean). Adapting traditional PBT led to overcoming the problems in the conventional PBT system in terms of large size. It achieved an acceptable reduction in bytes for the deterministic part (M, Indx) of over 400 bytes and the deterministic part (Res), where the size was reduced to more than 5000 bytes on average. The size has been reduced by nearly 50% compared to traditional PBT. The tested results indicate higher quality compared to the standard JPEG and traditional PBT in terms of performance. This includes a Compression Ratio (CR) of 13 and a PSNR of 48 dB.

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Developed JPEG Algorithm Applied in Image Compression

Cited by 9 publications

References 10 publications

The multi-quantization process with matrix size reduction is applied to compress images with strip structure light that is commonly used in 3D reconstructions

The multi-quantization process with matrix size reduction is applied to compress images with strip structure light that is commonly used in 3D reconstructions

Image Signal Decomposition Using Polynomial Representation with Hybrid Lossy and Non-Lossy Coding Scheme

Adaptive Pixel-Based Technique for Grayscale Image Compression

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