This paper proposes a new method to improve contrast of a mammogram using multi-energy x-ray (MEX) images. The
x-ray attenuation differences among breast tissues increase as incident photons have lower energy. Thus an image
obtained by a narrow low energy spectrum has higher contrast than a full (wide) energy spectrum image. The proposed
mammogram enhancement utilizes this fact using MEX images. Lowpass data of a low energy spectrum image and high
frequency components of a wide energy spectrum image are combined to have high contrast and low noise.
Nonsubsampled contourlet transform (NSCT) is employed to decompose image data into multi-scale and multidirectional
information. The NSCT overcomes the shortage of directions of wavelet transform by expressing smoothness
along contours sufficiently. The outcome of the transform is a lowpass subband and multiple bandpass directional
subbands. First, the lowpass subband coefficients of a wide energy spectrum image are substituted by those of a low
energy spectrum image. Before the coefficient modification, the low energy spectrum image is processed to have high
contrast and sharp details. Next, for the bandpass directional subbands, the locally adaptive bivariate shrinkage of
contourlet coefficients is applied to suppress noise. The bivariate shrinkage function exploits interscale dependency of
coefficients. Local contrast of the resultant mammogram is considerably enhanced and shows clear fibroglandular tissue
structures. Experimental results illustrate that the proposed method produces a high contrast and low noise level image,
as compared to the conventional mammography based on a single energy spectrum image.
Breast soft tissues have similar x-ray attenuations to mass tissue. Overlapping breast tissue structure often obscures mass
and microcalcification, essential to the early detection of breast cancer. In this paper, we propose new method to generate
the high contrast mammogram with distinctive features of a breast cancer by using multiple images with different x-ray
energy spectra. On the experiments with mammography simulation and real breast tissues, the proposed method has
provided noticeable images with obvious mass structure and microcalifications.
On a plasma display panel (PDP), luminous elements of red, green, and blue have different time responses. Therefore, a colored trails and edges appear behind and in front of moving objects. In order to reduce the color artifacts, this paper proposes a motion-based discoloring method. Discoloring values are modeled as linear functions of a motion vector to reduce hardware complexity. Experimental results show that the proposed method has effectively removed the colored trails and edges of moving objects. Moreover, the clear image sequences have been observed compared to the conventional ones.