Since the standardization of the JPEG 2000, it has found its way into many different applications such as DICOM (digital imaging and communication in medicine), satellite photography, military surveillance, digital cinema initiative, professional video cameras, and so on. The unified framework of the JPEG 2000 architecture makes practical high quality real-time compression possible even in video mode, i.e. motion JPEG 2000. In this paper, we present a study of the compression impact using dynamic code block size instead of fixed code block size as specified in the JPEG 2000 standard. The simulation results show that there is no significant impact on compression if dynamic code block sizes are used. In this study, we also unveil the advantages of using dynamic code block sizes.
JPEG 2000 is the new standard for image compression. The features of this standard makes it is suitable for imaging and
multimedia applications in this era of wireless and Internet communications. Discrete Wavelet Transform and embedded
bit plane coding are the two key building blocks of the JPEG 2000 encoder. The JPEG 2000 architecture for image
compression makes high quality compression possible in video mode also, i.e. motion JPEG 2000. In this paper, we
present a study of the compression impact using variable code block size in different levels of DWT instead of fixed
code block size as specified in the original standard. We also discuss the advantages of using variable code block sizes
and its VLSI implementation.
A novel rate-distortion optimization algorithm for JPEG 2000 is proposed. This algorithm meets memory buffer requirement for the compressed bit streams quite strictly according to a given bit rate. Moreover, before the encoding process even starts, a required memory buffer size can be estimated. This algorithm can also help avoid unnecessary encoding for some parts of an image. In this sense, it is memory efficient and performs progressive encoding. While a rate-distortion optimization algorithm is generally applied after complete encoding procedures for images in JPEG 2000, the proposed algorithm can save both memory requirement and encoding time significantly at low bit rate by avoiding complete encoding.
In an electronic color imaging device such as a digital camera using a single CCD or CMOS sensor, the color information is usually acquired in sub-sampled patterns of red (R), green (G) and blue (B) pixels. Full resolution color is subsequently generated from this sub-sampled image. This is popularly called Color Interpolation or Color Demosaicing. In this paper, we present a color interpolation algorithm using the method of fuzzy membership assignment along with the concept of smooth hue transition. The algorithm is adaptive in nature and produces superior quality full resolution color images compared to most of the popularly known color interpolation algorithms in the literature. Performance of the algorithm has been compared with a previously proposed block matching algorithm for color interpolation by the authors as well as the popularly used bilinear color interpolation. We present the results of comparison with some challenging sub-sampled images for color interpolation.
In an electronic color image capturing device using a single CCD or CMOS sensor, the color information is usually acquired into three sub-sampled color planes such as Red (R), Green (G) and Blue (B). Full resolution color is subsequently generated from this sub-sampled image using a suitable 'color interpolation' methodology. The color accuracy and appearance of the image is significantly affected by the color interpolation algorithm used to generate the full-resolution color image. In this paper, we present a new block matching based algorithm for color interpolation. The computational complexity of this algorithm is very low and hence suitable for real-time implementation in a portable image capture device e.g. a digital camera. The proposed algorithm produces the similar or better quality color images compared to most of the known color interpolation algorithms in the literature. We have presented results of comparison of the performance of the proposed algorithm with median interpolation and bilinear interpolation which are commonly used in practice.