A method that integrates tone mapping for high dynamic range (HDR) gray-scale images with JPEG
compression is proposed. The tone mapping operator (TMO) is block-based, and structured so that
the same discrete cosine transform (DCT) that is used for the JPEG compression serves to complete
a major part of the tone-mapping operation. Simulations have been done on high dynamic range
images from the Debevec library. Experimental results show the technique successfully tone maps
and compresses simultaneously; the number of bits per pixel is reduced from 32 to an average of
0.67 by the compression, with an average PSNR of 56.3 dB for the compressed tone-mapped images
compared to images that have been only tone-mapped. The output of the proposed method is an
image that requires only limited storage space, and can be decompressed with a standard JPEG
decoder.
This paper describes the design of analog circuitry to implement logarithmic number system (LNS) subtraction. Such
circuitry, if incorporated in the readout circuitry of a logarithmic CMOS image sensor, would allow for the on-chip
calculation of spatial derivatives, while operating directly on logarithmically-scaled pixels. The circuit was implemented
for a 1.2μm CMOS process. The maximum relative error at the output of the LNS subtractor for pixel currents that
correspond to an illumination range of more than four decades is 4.26%.
In this paper, a low-cost digital image correlation-based constitutive sensor with a novel identification algorithm that is
deployable and scalable in the field is proposed. The term 'constitutive sensor' is coined herein to describe a sensor that
is capable of determining the target material constitutive parameters. The proposed method is different from existing
identification methods in that it does not need to solve boundary value problems of the target materials using updated
parameters. Since the development of the digital image correlation (DIC) technique in the 1980s, the DIC technique has
been broadly evaluated and improved for measuring full-field displacements of test specimens, mainly in laboratory
settings. Although its potential in damage and mechanical identification is immense, the high cost of current commercial
DIC systems makes it difficult to apply the DIC technique to in-field health monitoring of structures. To realize a first
ever application of DIC in the field, a prototypical low-cost sensing unit consisting of a high performance embedded
microprocessor board, a low-cost web camera, and a communication module is suggested. In the proposed constitutive
sensor, DIC displacement fields considered as true values are used in computing stress fields satisfying the equilibrium
condition and strain fields using finite element concepts. The unknown constitutive law is initially assumed to be fully
anisotropic and linear elastic. A steady state genetic algorithm is utilized to search for the material parameters by
minimizing a cost function that measures energy residuals. The main features that allow the sensor to be deployable in
the field are introduced, and a validation of the proposed constitutive sensor concept using synthetic data is presented.
In this paper, a wavelet entropy based damage identification method is experimentally validated using wireless smart
sensor units (Imote2) with TinyOS-based firmware. Recently, the wireless smart sensor network has drawn significant
attention for applications in Structural Health Monitoring (SHM). Wavelet entropy is considered to be a damagesensitive
signature that can be obtained both at different spatial locations and time stations to indicate changes in
dynamic responses of structures. Compared to metrics based on the Fourier Transform, metrics based on wavelets
require much simpler mathematics, with no complex numbers. Thus wavelet-based SHM methods would be easier to
embed on motes. Wavelets can have other (mathematical) advantages when the structures are complex and the dynamic
signals are non-stationary. Particularly, use of the relative wavelet entropy (RWE) has been extensively explored for use
in damage detection using wireless smart sensors. First, sensor validation tests have been conducted using wireless and
wired sensors. To verify an off-line time synchronization technique and the feasibility of using acceleration data from
wireless sensors, modal identifications have been conducted using the ERA technique. Finally, the wavelet entropy
based damage detection method has been demonstrated using Imote2 wireless smart sensors.
This paper introduces a novel algorithm for the enhancement of images of large dynamic range. In addition to dynamic range compression, the method provides control of brightness and contrast. The dynamic range compression is done in the spatial domain using the log transformation. Brightness and contrast control are done in the biorthogonal 9/7 wavelet transform domain. The algorithm can be easily added on to a JPEG2000 image compression system with only a
modest increase in the computational complexity. Experimental results have shown comparable visual quality with the previously published Retinex algorithm.
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