Digital Image Processing: A Practical Introduction Using JavaEffordDigital image processing is not a new phenomenon: techniques for the manipulation, correction and enhancement of digital images have been in practical use for over 30 years and the underlying theoretical ideas have been around far longer. We don't have to look far these days to see an example of image processing at work. It has insinuated itself into many different areas of human endeavour, ranging from small-scale activities such as desktop publishing and healthcare, through to activity on the largest scales imaginable - the search for natural resources on the Earth, or the study of other planets, stars and galaxies.Many existing texts give this subject a strong electrical engineering or physics perspective, or present a rigorous treatment that can be comprehended fully only by a reader possessing advanced mathematical skills. Others adopt a less theory-based, more practical approach, but lack the examples or the software tools that would allow readers to develop their own image processing applications; and, where software tools are provided, they are often inflexible or platform dependent.The aim of this book is to provide a practical introduction to image processing, avoid |
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8-bit greyscale images AffineTransform algorithm amplitude application array ASCII binary images blurred boolean BufferedImage BufferedImage image byte calculation Canny edge detector Chapter codewords colour images command line components compression ratio computed constructor convolution convolution kernel ConvolutionOp Convolve ConvolveOp create deflation algorithm dest dilation dimensions display double edge detection encoder Equation erosion example Figure float format Fourier transform function Gaussian gradient magnitude grey level grey level mapping high pass filter Huffman coding image data image processing ImageFFT implementation input image int h integer interface interpolation Java2D JPEG Listing low pass filter mean grey level median filter method neighbourhood noise null operations output image parameter perform pixel data pixel grey level pixel values public static quantisation range Raster region represented rescaling result rotation sampling segmentation setPixel shows simple sinusoidal spatial frequency specified spectrum storage stored structuring element techniques threshold void warping width zero