Subband coding is a powerful means for highly efficient image compression. In order to improve the coding performance of subband image coding, we recently have proposed the optimum space-frequency partition coder (OSFP) that optimizes the following three factors in the rate-distortion sense: the frequency band partition with a small number of subbands, quantization and the spatial segmentation to exclude redundant pixels. However, an encoded image obtained by OSFP is not necessarily optimal in subjective image quality because the three factors are optimized to minimize the mean square error (MSE). In this paper, we present a new OSFP that obtains a high quality coded image subjectively by optimizing the three factors so that MSE weighted by considering both the human visual sensitivity and a region-of-interest of human is minimized. Experimental results show that the quality of encoded images obtained by the proposed method has higher subjectively than them of both the conventional OSFP and JPEG2000 by the mean opinion score (MOS).
As digital imaging becomes more widespread in a variety of industries, new standards for measuring resolution and sharpness are being developed. Some differ significantly from ISO 12233:2014 Modulation Transfer Function (MTF) measurements. We focus on the ISO 16505 standard for automotive Camera Monitor Systems, which uses high contrast hyperbolic wedges instead of slantededges to measure system resolution, defined as MTF10 (the spatial frequency where MTF = 10% of its low frequency value). Wedges were chosen based on the claim that slanted-edges are sensitive to signal processing. While this is indeed the case, we have found that wedges are also highly sensitive and present a number of measurement challenges: Sub-pixel location variations cause unavoidable inconsistencies; wedge saturation makes results more stable at the expense of accuracy; MTF10 can be boosted by sharpening, noise, and other artifacts, and may never be reached. Poor quality images can exhibit high MTF10. We show that the onset of aliasing is a more stable performance indicator, and we discuss methods of getting the most accurate results from wedges as well as misunderstandings about low contrast slanted-edges, which correlate better with system performance and are more representative of objects of interest in automotive and security imaging.
2.5D printing is a technology which creates surface relief by superimposing successive layers of inks. The question of the characterization of heights obtained with this technique brings us to consider new metrics and mathematical ways to represent the influence of diverse printing parameters on the obtained relief, possibly used to compensate the defaults of the system. Our method takes over the classical Modulation Transfer Function (MTF) approach and adapts it to a vertical modulation instead of considering the (x, y) plane, introducing then a Height Modulation Transfer Function (HMTF). Characterization charts are composed of lines patterns printed at different heights, frequencies and droplet levels. Prints are scanned with a chromatic confocal sensor and resulting topographies are analyzed to extract the HMTF. By analogy with traditional MTF methods, results – consisting of the measurement of the deviation between the digital input and the analog output – allow to evaluate the quality of our printer and to compensate it by setting up a retro-action loop. The method, here presented in the case of the 2.5D printing prototype, can be extended to regular 3D printing techniques.