Monagi H. Alkinani^1,*, E. A. Zanaty², Sherif M. Ibrahim³

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1577-1593, 2021, DOI:10.32604/cmc.2021.014803

Abstract This paper presents a novel method utilizing wavelets with particle swarm optimization (PSO) for medical image compression. Our method utilizes PSO to overcome the wavelets discontinuity which occurs when compressing images using thresholding. It transfers images into subband details and approximations using a modified Haar wavelet (MHW), and then applies a threshold. PSO is applied for selecting a particle assigned to the threshold values for the subbands. Nine positions assigned to particles values are used to represent population. Every particle updates its position depending on the global best position (gbest) (for all details subband) and local best position (pbest) (for… More >

Nancy Awadallah Awad^1,*, Amena Mahmoud²

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3151-3160, 2021, DOI:10.32604/cmc.2021.014426

Abstract Data compression is one of the core fields of study for applications of image and video processing. The raw data to be transmitted consumes large bandwidth and requires huge storage space as a result, it is desirable to represent the information in the data with considerably fewer bits by the mean of data compression techniques, the data must be reconstituted very similarly to the initial form. In this paper, a hybrid compression based on Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) is used to enhance the quality of the reconstructed image. These techniques are followed by entropy encoding such… More >

Xintao Duan^{1, *}, Daidou Guo¹, Chuan Qin²

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.2, pp. 721-745, 2020, DOI:10.32604/cmes.2020.09463

Abstract Image steganography is a technique that hides secret information into the cover image to protect information security. The current image steganography is mainly to embed a smaller secret image in an area such as a texture of a larger-sized cover image, which will cause the size of the secret image to be much smaller than the cover image. Therefore, the problem of small steganographic capacity needs to be solved urgently. This paper proposes a steganography framework that combines image compression. In this framework, the Vector Quantized Variational AutoEncoder (VQ-VAE) is used to achieve the compression of the secret image. The… More >

F. Keissarian¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.12, No.4, pp. 137-144, 2009, DOI:10.3970/icces.2009.012.137

Abstract In this paper, a new image compression technique is proposed in which variable block size technique is adopted, using quadtree decomposition, for coding images at low bit rates. The proposed algorithm decomposes the host image into blocks of variable sizes according to histogram analysis of the block residuals. Variable block sizes are then encoded at different rates based on their visual activity levels. To preserve edge integrity, a high-detail block is coded by a set of parameters associated with the pattern appearing inside the block. The use of these parameters at the receiver together with the quadtree code reduces the… More >

Abdurazzag Ali Aburas¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.9, No.1, pp. 1-2, 2009, DOI:10.3970/icces.2009.009.001

Abstract The typical Optical Character Recognition (OCR) systems, regardless the character's nature, are based mainly on three stages, preprocessing, features extraction and discrimination (recognizer). Each stage has its own problems and effects on the system efficiency such as time consuming and recognition errors. In order to avoid these difficulties this talk presents new construction of OCR system without pre-processing, features extraction and classifier for any handwriting characters using standard and advanced Image Compression techniques. The proposed algorithms obtained promising results in terms of accuracy as well as in terms of time consuming. More >

Mohammed Omari^1,*, Souleymane Ouled Jaafri¹

CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 753-775, 2019, DOI:10.32604/cmc.2019.06576

Abstract Image compression is a process based on reducing the redundancy of the image to be stored or transmitted in an efficient form. In this work, a new idea is proposed, where we take advantage of the redundancy that appears in a group of images to be all compressed together, instead of compressing each image by itself. In our proposed technique, a classification process is applied, where the set of the input images are classified into groups based on existing technique like L₁ and L₂ norms, color histograms. All images that belong to the same group are compressed based on dividing… More >

Jun Zhang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.22, No.2, pp. 91-96, 2007, DOI:10.3970/cmes.2007.022.091

Abstract The most commonly used wavelets for image processing are the tensor-product of univariate wavelets, which have a disadvantage of giving a particular importance to the horizontal and vertical directions. In this paper, a new class of wavelet, non-separable wavelet, is investigated for image compression applications. The comparative results of image compression preprocessed with two different kinds of wavelet transform are presented: (1) non-separable wavelet transform; (2) tensor-product wavelet transform. The results of our experiments show that in the same vanishing moment, the non-separable wavelets perform better than the tensor-product wavelets in dealing with still images. More >