It has been investigated that at low bit rates, downsampling prior to coding and upsampling after decoding can achieve better compression performance than standard coding algorithms, e.g., JPEG and H. 264/AVC. However, at high bit rates, the sampling-based schemes generate more distortion. Additionally, the maximum bit rate for the sampling-based scheme to outperform the standard algorithm is image-dependent. In this paper, a practical adaptive image coding algorithm based on the cubic-spline interpolation (CSI) is proposed. This proposed algorithm adaptively selects the image coding method from CSI-based modified JPEG and standard JPEG under a given target bit rate utilizing the so called ρ-domain analysis. The experimental results indicate that compared with the standard JPEG, the proposed algorithm can show better performance at low bit rates and maintain the same performance at high bit rates.
Cubic-spline interpolation (CSI) scheme is known to be designed to resample the discrete image data based on the leastsquares
method with the cubic convolution interpolation (CCI) function. It is superior in performance to other
interpolation functions for digital image processing. In this paper, an improved CSI scheme that combines the leastsquares
method with an eight-point cubic interpolation kernel is developed in order to improve the performance of the
original CSI scheme. Either the FFT/Winograd DFT or the fast direct computation algorithm can also be used to perform
the circular convolution needed in this improved CSI scheme. Furthermore, its correlated image data and auto-correlated
filter coefficients are also accurately calculated in this paper. Experimental results indicate that the proposed improved
CSI scheme yields a much better quality of reconstructed image than existing interpolation algorithms.
In this paper, a simplified decoding algorithm to correct both errors and erasures is used in conjunction with the
Euclidean algorithm for efficiently decoding nonsystematic RS codes. In fact, this decoding algorithm is an appropriate
modification to the algorithm developed by Shiozaki and Gao. Based on the ideas presented above, a fast algorithm
described from Blahut's classic book is derivated and proved in this paper to correct erasures as well as errors by
replacing the Euclidean algorithm by the Berlekamp-Massey (BM) algorithm. In addition, computer simulations show
that this simple and fast decoding technique reduces the decoding time when compared with existing efficient algorithms
including the new Euclidean-algorithm-based decoding approach proposed in this paper.
The quadratic residue codes are a class of the error correcting codes with interesting mathematics. Among them, the (31,
16, 7) quadratic residue code is the code with reducible generator polynomial and three-error-correcting capacity. The
algebraic decoding algorithm for the (32, 16, 8) quadratic residue code is developed by Reed et al. (1990). In this paper,
a simplified decoding algorithm is proposed. The algorithm uses bit-error probability estimates, which is first developed
by Reed MIT Lincoln Laboratory Report (1959), to cancel the third error and then uses the algebraic decoding algorithm
mentioned above to correct the remaining two errors. Simulation results show that this modified decoding algorithm
slightly reduces the decoding complexity for correcting the third error while maintaining the same BER performance in
additive white Gaussian noise (AWGN). Also, the flowchart of the above decoding algorithm is illustrated with Fig. 1.
An enhanced wavelet-based compression scheme for satellite image is proposed in this paper. The Consultative
Committee for Space Data System (CCSDS) presented a recommendation which utilizes the wavelet transform and the
bit plane coder for satellite image compression. The bit plane coder used in the CCSDS recommendation encodes the
coefficient block of bit planes one by one and then truncates the unnecessary bit plane coefficient blocks. By this way,
the contexts of bit planes are not considered as the redundancy embedded data which may be compressed further. The
proposed scheme uses a bit plane extractor to parse the differences of the original image data and its wavelet transformed
coefficients. The output of bit plane extractor will be encoded by a run-length coder and will be sent to the
communication channel with the CCSDS compressed data. Comparing with the recommendation of CCSDS, under a
reasonable complexity, the subjective quality of the image will maintained or even better. In addition, the bit-rate can be
further decreased from 85% to 95% of the CCSDS image compression recommendation at the similar objective quality
level. By using the lower bit rate lossy mode compression and bit plane compensation, it is possible to obtain lower bit
rate and higher quality image than which the higher bit rate lossy mode compression can achieve.
In this paper, a near lossless medical image compression scheme combining JPEG-LS with cubic spline interpolation (CSI) is presented. The CSI is developed to subsample image data with minimal distortion and to achieve image compression. It has been shown in literatures that the CSI can be combined with the transform-based image compression algorithm to develop a modified image compression codec, which obtains a higher compression ratio and a better subjective quality of reconstructed image than the standard transform-based codecs. This paper combines the CSI with lossless JPEG-LS to form the modified JPEG-LS scheme and further makes use of this modified codec to medical image compression. By comparing with the JPEG-LS image compression standard, experimental results show that the
compression ratio increased over 3 times for the proposed scheme with similar visual quality. The proposed scheme reduces the loading for storing and transmission of image, therefore it is suitable for low bit-rate telemedicine application. The modified JPEG-LS can reduce the loading of storing and transmitting of medical image.
In this paper, a modified image compression algorithm using cubic spline interpolation (CSI) and bit-plane compensation
is presented for low bit-rate transmission. The CSI is developed in order to subsample image data with minimal
distortion and to achieve image compression. It has been shown in literatures that the CSI can be combined with the
JPEG or JPEG2000 algorithm to develop a modified JPEG or JPEG2000 CODEC, which obtains a higher compression
ratio and better quality of reconstructed images than the standard JPEG and JPEG2000 CODECs in low bit-rate range.
This paper implements the modified JPEG algorithm, applies bit-plane compensation and tests a few images.
Experimental results show that the proposed scheme can increase 25~30% compression ratio of original JPEG data
compression system with similar visual quality in low bit-rate range. This system can reduce the loading of
telecommunication networks and is quite suitable for low bit-rate transmission.
In this paper, a modified medical image compression algorithm using cubic spline interpolation (CSI) is presented for
telemedicine applications. The CSI is developed in order to subsample image data with minimal distortion and to
achieve compression. It has been shown in literatures that the CSI can be combined with the JPEG algorithms to
develop a modified JPEG codec, which obtains a higher compression ratio and a better quality of reconstructed image
than the standard JPEG. However, this modified JPEG codec will lose some high-frequency components of medical
images during compression process. To minimize the drawback arose from loss of these high-frequency components,
this paper further makes use of bit-plane compensation to the modified JPEG codec. The bit-plane compensation
algorithm used in this paper is modified from JBIG2 standard. Experimental results show that the proposed scheme can
increase 20~30% compression ratio of original JPEG medical data compression system with similar visual quality. This
system can reduce the loading of telecommunication networks and is quite suitable for low bit-rate telemedicine
In this paper, a new medical image compression algorithm using cubic spline interpolation (CSI) is presented for
telemedicine applications. The CSI is developed in order to subsample image data with minimal distortion and to
achieve image compression. It has been shown in literatures that the CSI can be combined with the JPEG or JPEG2000
algorithm to develop a modified JPEG or JPEG2000 codec, which obtains a higher compression ratio and a better
quality of reconstructed image than the standard JPEG and JPEG2000 codecs. This paper further makes use of the
modified JPEG codec to medical image compression. Experimental results show that the proposed scheme can increase
25~30% compression ratio of original JPEG medical data compression system with similar visual quality. This system
can reduce the loading of telecommunication networks and is quite suitable for low bit-rate telemedicine applications.
This paper proposed an adaptive wavelet-based deblocking algorithm for MPEG-4 video coding standard. The novelty of this method is that the deblocking filter uses a wavelet-based threshold to detect and analyze artifacts on coded block boundaries. This threshold value is based on the difference between the wavelet transform coefficients of image blocks and the coefficients of the entire image. Therefore, the threshold value is made adaptive to different images and characteristics of blocking artifacts. Then one can attenuate those artifacts by applying a selected filter based on the above threshold value. It is shown in this paper that the proposed method is robust, fast, and works remarkably well for MPEG-4 codec at low bit rates. Another advantage of the new method is that it retains sharp features in the decoded frames since it only removes artifacts. Experimental results show that the proposed method can achieve a significantly improved visual quality and increase the PSNR in the decoded video frame.
In this paper, the cubic spline interpolation (CSI) is shown to be performed by a direct computation for the encoding and decoding processes of image coding. A pipeline structure can be used to implement this new CSI. Such a new CSI algorithm can be used along with the JPEG standard to obtain the new CSI-JPEG codec and while still maintaining good quality of the reconstructed image for higher compression ratios. In this paper, it is shown that this new CSI-JPEG codec makes possible a pipeline compression algorithm that is naturally suitable for hardware implementation.
This paper develops a bit-plane coding technique to achieve the subtitle enhancement in MPEG-4 for very low bit rate streaming video. The original video frame that contains subtitle information is encoded by the use of MPEG-4 codec and then the MPEG-4 decoded Y frame is subtracted from the original one to generate a residue. Because the subtitle information usually appears on the special region of a video frame, one can pre-set the position of the subtitle region and just process this residue subtitle region for subtitle enhancement. The pixel value of the residue subtitle region will be transferred from decimal number to binary number. Thus one can obtain 8 bit-planes of the residue subtitle region. For each bit-plane, (RUN, EOP) symbols are formed and then encoded via the variable length coding to produce the output bitstream. It has been shown that such a bit-plane coding technique is very efficient and its decoding procedure can be easily performed. From various experimental results, using MSB, MSB-1 and MSB-2 planes can obtain a satisfied subtitle visual enhancement with only increasing 5% bit rate.
Proc. SPIE. 4474, Advanced Signal Processing Algorithms, Architectures, and Implementations XI
KEYWORDS: Signal to noise ratio, Switches, Remote sensing, Telecommunications, Very large scale integration, Compact discs, Digital video discs, Algorithm development, Data communications, Computer architecture
The inverse-free Berlekamp-Massey (BM) algorithm is the simplest technique for Reed-Solomon (RS) code to correct errors. In the decoding process, the BM algorithm is used to find the error locator polynomial with syndromes as the input. Later, the inverse-free BM algorithm is generalized to find the error locator polynomial with given erasure locator polynomial. By this means, the modified algorithm can be used for RS code to correct both errors and erasures. The improvement is achieved by replacing the input of the Berlekamp-Massey algorithm with the Forney syndromes instead of the syndromes. With this improved technique, the complexity of time domain RS decoders for correcting both errors and erasures is reduced substantially from previous approaches. In this paper, the register transfer language of this modified BM algorithm is derived and the VLSI architecture is presented.
In this paper, a fast algorithm is developed which reduces the searching space for Fractal image coding. The basic idea is to classify the domain pool into three classes, non- edged class, horizontal/vertical class and the diagonal class. For each given range block, the property is computed first to determine which class it belongs. Then one only has to search from the corresponding class in the domain pool to find the best match. The classification operation is performed only according to the lowest frequency coefficients of the given block in the horizontal and vertical directions, in which the frequency data is computed from Discrete Cosine Transform (DCT). The main advantages for this classification scheme are that the classification mechanism is simple and the DCT algorithm is easy to implement. A simulation shows that, the proposed fast algorithm is about 2 times faster than the baseline method while the quality of the retrieved image is almost the same.