Aspose.Imaging for Python via .NET 25.4 - Release notes

### Example
The images, which appear dull and lack sufficient brightness due to an underutilized color range, can have their perceived quality significantly improved by applying a histogram normalization filter. This technique adjusts the image to fully utilize the entire available color spectrum, enhancing both contrast and visual appeal. 

To further enhance the contrast of the image, you can utilize the **RasterImage.adjust_contrast(contrast:float)** method, where the contrast value ranges from -100 to 100. This allows for fine-tuned control over the image's contrast, enabling both subtle and dramatic improvements as needed.

from aspose.imaging import Image, RasterImage
from aspose.pycore import as_of

inputFilePath = "input.png"
outputFilePath = "output.png"
outputFilePath2 = "output2.png"
with as_of(Image.load(inputFilePath), RasterImage) as image:
	image.normalize_histogram()
	image.save(outputFilePath)
	image.adjust_contrast(30)
	image.save(outputFilePath2)

from aspose.imaging import Image

with Image.load("00506.dcm") as image:
    image.save("00506.dcm.jpg")

from aspose.imaging import Image, TextRenderingHint, SmoothingMode
from aspose.imaging.imageoptions import JpegOptions, CmxRasterizationOptions, PositioningTypes

with Image.load("saffah khan cmx.cmx") as image:
    jpeg_options = JpegOptions()
	cmx_options = CmxRasterizationOptions()
    cmx_options.text_rendering_hint = TextRenderingHint.SINGLE_BIT_PER_PIXEL
    cmx_options.smoothing_mode = SmoothingMode.ANTI_ALIAS
    cmx_options.positioning = PositioningTypes.RELATIVE
    jpeg_options.vector_rasterization_options = cmx_options
	image.save("saffah khan cmx.cmx.jpg", jpeg_options)