Haze is when fine particles like smoke, dust, and water droplets in the air make it difficult to see clearly and distort light. This can affect the sharpness, contrast, and colors in pictures. To fix this, we've come up with a new way to remove haze from both remote sensing and regular images. We start by breaking the image into patches (small groups of pixels) and figuring out the atmospheric light for each patch. Then, we smooth it using a guided filter. After that, we calculate the transmission map using an improved dark channel prior, which includes a dark channel prior and a combined window filter to reduce unwanted effects. We tested this method on images from the ground and remote sensing, and it worked well. So, our method can restore images by dealing with uneven atmospheric light, minimizing unwanted effects, and producing clear, detailed, and natural-looking results.