A Novel Spatial Domain Lossless Image Compression Scheme
نویسندگان
چکیده
In present Multimedia Computing era, compression of multimedia data has been highly significant. Digital Image, being a major part of multimedia data, requires effective compression mechanisms as well. During last few decades, there had been innovated numerous image compression techniquesmost of which achieve considerable compression ratio by taking the advantage of domain transformation. Very few image compression algorithms are yet developed that can achieve appreciable compression ratio without transforming the image from the spatial domain. In this paper, we present a novel lossless image compression technique that does not require domain transformation. In spatial domain, it separates the image into blocks, performs some preprocessing and finds the Largest Differenced Pixel (LDP) value of a block. The amount of compression that can be achieved depends merely on the maximum differenced pixel value of the block. Apart from saving a notable amount of time required for domain transformation, experimental results over 200 standard images reveal that our proposed technique achieves 5.96% compression ratio on an average for gray-scale images while 11.69% average compression ratio for color images. Comparative studies of some particular test images prove the efficiency of the devised mechanism as compared to the existing spatial domain image compression algorithms. Finally, MSE calculation ensures the decompressed image is an exact approximation of the raw image considered for compression.
منابع مشابه
فشردهسازی تصویر با کمک حذف و کدگذاری هوشمندانه اطلاعات تصویر و بازسازی آن با استفاده از الگوریتم های ترمیم تصویر
Compression can be done by lossy or lossless methods. The lossy methods have been used more widely than the lossless compression. Although, many methods for image compression have been proposed yet, the methods using intelligent skipping proper to the visual models has not been considered in the literature. Image inpainting refers to the application of sophisticated algorithms to replace lost o...
متن کاملLossless Microarray Image Compression by Hardware Array Compactor
Microarray technology is a new and powerful tool for concurrent monitoring of large number of genes expressions. Each microarray experiment produces hundreds of images. Each digital image requires a large storage space. Hence, real-time processing of these images and transmission of them necessitates efficient and custom-made lossless compression schemes. In this paper, we offer a new archi...
متن کاملAn Improved Approach for Spatial Domain Lossless Image Data Compression Method by Reducing Overhead Bits
Lossless image compression techniques are used in digital imaging where large amount of data is to be stored without compromising the image quality. The volume of data that can be compressed using lossless image compression schemes is usually much lesser than that of its lossy compression counterparts. Yet, however, lossless compression algorithms are popular in a number of particular image dat...
متن کاملRank order polynomial decomposition for image compression
In this paper, a novel decomposition scheme for image compression is presented. It is capable to apply any nonlinear model to compress images in a lossless way. Here, a very efficient polynomial model that considers spatial information as well as order statistic information is introduced. This new rank order polynomial decomposition (ROPD) that allows also for a progressive bitstream is applied...
متن کاملModifying integer wavelet transforms for scalable near-lossless image coding
In near-lossless image coding, each reconstructed pixel of the decoded image differs from the corresponding one in the original image by not more than a pre-specified value δ. Such schemes are mainly based on predictive coding techniques, which are not capable of scalable decoding. Lossless image coding with scalable decoding is mainly based on integer wavelet transforms. In this paper, methods...
متن کامل