This paper presents a novel formulation of the classical mean filtering, which has been shown to stem from the theory of continued fractions as well as from the rules of binomial expansion.
Such an alternative formulation of mean filtering is marked by its sufficiency of only a few primitive operations, namely binary shifts and addition (subtraction), in the integer domain.
Subsequently, the resultant process of smoothing a digital image using the mean filter is devoid of any floating-point computation, and can be implemented by a simple hardware, thereof.
In addition, the formulation has the ability of yielding an approximate solution using fewer operations, which can bring the hardware cost further down.
We have tested our method for various images, and have reported some
relevant results to demonstrate its elegance, versatility, and effectiveness, specially when an approximate solution is called for.
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.
To overcome many drawbacks in the current JPEG standard for still image compression, a new standard, JPEG2000, is under development by the International Standard Organization. Embedded bit plane coding is the heart of the JPEG2000 encoder. This encoder is more complex and has significantly higher computational requirements compared to the entropy encoding in current JPEG standard. Because of the inherent bit-wise processing of the entropy encoder in JPEG2000, memory traffic is a substantial component in software implementation. However, in hardware implementation, the lookup tables can be mapped to logic gates and memory accesses for the state bit computation can be reduced significantly by careful design. In this paper, we present an efficient VLSI architecture for embedded bit-plane coding in JPEG2000 that reduces the number of memory accesses. To better understand the interaction of this architecture with the rest of the coder, we also present a system level architecture for efficient implementation of JPEG2000 in hardware.
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.
Proc. SPIE. 3963, Color Imaging: Device-Independent Color, Color Hardcopy, and Graphic Arts V
KEYWORDS: Sensors, Matrices, Interference (communication), Control systems, Image sensors, Measurement devices, Human vision and color perception, Digital recording, Environmental sensing, Color reproduction
As the spectral sensitivities of most color devices are typically different from that of human vision or corresponding output devices, signals from different channels (such as Red, Green and Blue) of a color recording device need to be properly mixed to generate color information suitable for viewing. The mixing (or transformation) which minimizes some error measure between the target and the transformed colors of a large set of color patches is normally used for this purpose. As the color error is the only criterion in determining such transformation, the measurement noises of the color device may often be amplified in the target color space without much control. We present in this paper a new color correction method that takes account of both the color error and the noise variance in reproduced images. This method is useful in applications where the measurement noises of recording devices are not necessarily low. The proposed method is then extended to include other color reproduction constraints. Analytical solutions and experimental results of the proposed method are both reported in the paper.
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.
We present a new high speed parallel architecture and its VLSI implementation to design a special purpose hardware for real-time lossless image compression/decompression using a decorrelation scheme. The proposed architecture can easily be implemented using state-of-the- art VLSI technology. The hardware yields a high compression rate. A prototype 1-micron VLSI chip based on this architectural idea has been designed. The scheme is favorably comparable to the JPEG baseline lossless image compression schemes. We also discuss the parallelization issues of the JPEG baseline standard still compression schemes and their difficulties.