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Bit-length of digital images is decided by the Analog-to-Digital (AD) converter. The bit-length expansion technique is necessary for high-quality displays such as the liquid crystal display (LCD) and the plasma display. Bit-length expansion is also necessary for low-bit length images, which are degraded by the pseudo-contour. In this paper, we propose a bit-length expansion method from M-level to N-level [N=3(M-1)+1]. This operation means that two quantization levels are introduced between existing levels. The bit-length expansion method results in the estimation problem of an error image between an M-level's image and an N-level's image. The error image is the pattern image which consists of three values. We show the estimation method of the three values pattern image and that the proposed method can remove the pseudo-contour of digital images through several application results. © 2009 Wiley Periodicals, Inc. Electron Comm Jpn, 92(10): 32–40, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecj.10105 [ABSTRACT FROM AUTHOR]

In the information and communications field, digital images have come to be widely used in mobile communications devices, and digital image processing is very important. Because of the different resolutions of the displays and output devices in each terminal, digital images undergo reduction and enlargement processing very frequently. Conventionally, reduction and enlargement processing is performed using an interpolation algorithm based on the sinc function. However, because the frequency band increases when digital images are enlarged, an enlarged image of sufficient quality cannot be attained through interpolation. In recent years, an enlargement method has been proposed which uses estimation of the frequency bands (high-frequency components) which increase with the enlargement of a digital image. The authors have also clarified interpolation algorithms using the preservation of step edge signals, coordinate point warping for generating peak signals, and signal amplitude biasing. They have implemented an interpolation algorithm which produces high-frequency components. In calculating the bias in this method, the smaller of the biases found to either side of the interpolation is selected. This choice is not necessarily optimal; the larger bias should be selected depending on certain conditions. For example, the selection of the larger bias makes it possible to preserve the precipitous changes in a step edge signal. This makes it possible to preserve step edge signals and generate peaks, without also using coordinate point warping, by selecting the optimal bias according to local information. The proposed interpolation algorithm using data-dependent biasing was compared to an interpolation algorithm using coordinate point warping and signal amplitude biasing. The proposed algorithm was found to have a similar performance and clearly shown to be a method with low computational complexity. © 2007 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 90(8): 18–28, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20306 [ABSTRACT FROM AUTHOR]

The YUV 4:2:0 format is a representative format for color images in international standards. In this format, both color difference components U and V reduce the number of pixels in the horizontal and vertical directions by one-half. Consequently, this reduction degrades the color difference components. At a relatively high bit rate, the degradation produced by reducing the number of pixels is often worse than the degradation that depends on the coding. Thus, processing to compensate for the degradation due to the format transform becomes necessary. The pixels of the color difference components reduced once on the encoding side are determined by interpolation on the decoding side. The typical interpolation methods are bilinear interpolation, bicubic interpolation, and interpolation by a finite impulse response (FIR) filter. When these interpolation methods were applied to interpolate the color difference components in the YUV 4:2:0 format, blur and lower saturation were produced in the colors in the color difference components returned to the original number of pixels. In this paper, we propose a method that uses information in the luminance component not having a reduced number of pixels to interpolate the color difference components in the YUV 4:2:0 format. Consequently, color blurring is prevented in the edges of the image, and an objective is to improve the saturation in the entire image. We based the proposed method on bilinear interpolation and bicubic interpolation, and formulated an interpolation method using the luminance component as an extended form. The proposed method and the bicubic interpolation are compared in both objective and subjective evaluations, and demonstrate the effectiveness of the proposed method. © 2006 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 89(9): 1–10, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20218 [ABSTRACT FROM AUTHOR]

When a multiscale digital image is output into a device with fewer simultaneous generation scales, such as two scales (black and white), halftoning is performed for approximate representation of the grayscale. A typical approach is the error diffusion method. Problems in this error diffusion method are the generation of regular patterns (worms) in the flat portion and of constant value regions not halftoned after variations where the signal varies suddenly. In this paper, the constant value region is investigated. A new method is proposed to avoid constant value regions. The constant value region is generated by diffusion of the quantization error with an inappropriate value for the forward scanning direction. In order to prevent this problem, the edge sections where generation of the constant value region is expected are eliminated by a smoothing filter. In this way, inappropriateness of the quantization error values for regions with different values in the forward scanning direction is suppressed. In order to prevent blurring of the input image, the filtering process is a data-dependent type that is limited to avoiding constant value regions. The proposed method is a simple one allowing avoidance of the constant value region without causing blurring by inserting a simple data-dependent prefilter. © 2006 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 89(5): 1–11, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20214 [ABSTRACT FROM AUTHOR]

Since the dimensions for digital images are set by the acquisition system, digital image enlargement is indispensable when the dimensions that can be displayed are larger in the display system than in the acquisition system. Conventionally, this enlargement process was performed by interpolation. The digital image enlargement corresponds to a larger Nyquist frequency, but the frequency band that is expanded during the enlargement cannot be considered by the interpolation scheme, and blur is produced in the enlarged image. The parts where the image blur stands out subjectively are primarily the signals forming the image contours having the step edge shape and the details of the image consisting of mountain- and valley-shaped signals when viewed microscopically. Therefore, the proposed method moves the coordinate points interpolated to preserve the discontinuities of step edge signals and decides whether the interpolated points are the vertices of the mountain- or valley-shaped signals, and then moves the amplitudes of the interpolated points for creating these peak signals up or down. In other words, we explain an interpolation scheme involving the warping and biasing that randomly moves the coordinate points and the signal amplitudes, and implement digital image interpolation with improved resolution. Furthermore, the parameter settings for the proposed method are both objectively and subjectively evaluated. © 2004 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 88(2): 10–21, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20095 [ABSTRACT FROM AUTHOR]

When a texture is considered as a set of granular components of various sizes and shapes, it is meaningful to determine its features in the spatial domain. It is known that such granular features in the spatial domain can be calculated by means of the pattern spectrum obtained by morphology operations. The pattern spectrum has the property that a peak exists at the point where the structuring element of the morphology filter agrees with the granular feature composing the texture. Utilizing this property, this paper proposes a method by which the features of the granules (shape and size) composing the texture are represented by a structuring element on the basis of pattern spectrum information. The proposed method restricts the textures to be analyzed to textures composed of granules of a single shape and size. A method of using the obtained model to decide whether the given texture can be analyzed is presented. With this approach, it is possible to decide whether or not the derived model represents the texture feature. © 2004 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 88(2): 31–40, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.10070 [ABSTRACT FROM AUTHOR]